The full text on this page is automatically extracted from the file linked above and may contain errors and inconsistencies.
SIXTH DISTRICT MANUFACTURING INDEX Technical Note and Statistical Supplement FEDERAL RESERVE BANK OF ATLANTA JUNE 1970 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis SIXTH DISTRICT MANUFACTURING PRODUCTION INDEX: Technical Note and Statistical Supplement Federal Reserve Bank of Atlanta Prepared by C. S. Pyun, Economist Research Department June 1970 ACKNOWLEDGMENTS It would not have been possible to complete this project without the work of a team of competent and cooperative individuals in the Miss Cheryl Odom and Miss Sally E. Barr have performed the ex Bank. cruciating task of collecting, sorting, and verifying a large volume They also calculated countless of the raw input data that were used. numbers of individual index series—both those series computed while the work was still in an experimental stage and those final series con tained in this note. They carried out these important tasks with maximum efficiency and a great deal of patience. Miss Martha Bethea and Mrs. Sara Anderson provided indispensable assistance and technical advice on a large volume of raw data which needed to be processed by computers. Mr. Robert Sexton of the Data Processing Department also offered advice and help in programming work. Mrs. Lane Chason spent many hours in verifying and correcting the electric power series used in the index construction. Mr. Milo Peterson, formally a staff member of the Board of Governors, Federal Reserve System, gave his time and expertise in unraveling many trouble some issues associated with using electric power statistics. While the project was in progress, Mrs. Sherley Wilson typed many pages of scribbled notes and tables and drew charts of many individual series. She also typed several drafts, as well as the final version of this note with her usual efficiency. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis TABLE OF CONTENTS Part I Section I - Introduction....................................................................................................... 1 Section II - Concept and Coverage.................................................................................... 3 Section III - Estimating Equations and Procedures................................................8 Section IV - Characteristics of the Estimating Equations.......................... 12 Section V - Data Sources and Limitations.............................................................. 16 Section VI - Empirical Validity of District ProductionIndex................... 21 APPENDIX A Table Table Table Table Table - Productivity Extrapolators................................................................... 26 - Industry Index Derivation..................................................................... 27 - Value Added by Manufactures, 1963.................................................. 28 - Factor Weights, 1963................................................................................. 29 - Linear Regression of Annual Man-hourProductivity, 1957-65................................................................................................................. 30 Table 6. - Relative Performance of District Production Indexes for Selected Industries...........................................................................31 1. 2. 3. 4. 5. Part II APPENDIX B - District Production Indexes, Seasonally Adjusted.............. 32 APPENDIX C - District Production Indexes, Seasonally Unadjusted......... 43 Bibliography....................................................................................................................................... 54 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis DISTRICT MANUFACTURING PRODUCTION INDEX Technical Note and Statistical Supplement This note consists of two major parts. Part I describes the concepts and methodology employed in constructing the new production index that was developed by the Research Department of the Federal Reserve Bank of Atlanta. Also included in Part I is a discussion of the empirical validity of the District production index. Part II contains, in time series form, indexes which are seasonally adjusted and unadjusted for individual industries and three major industrial groupings (i.e., durables, nondurables, and total manufacturing). Section I - Introduction Because of their unique participation in formulating national monetary policies, individual District Reserve Banks have been vitally interested in the development and compilation of various economic statistics germane to the study of their regions. The search for various comprehensive measure ments that can be used as a broad foundation for regional economic analysis, such as one that reflects an up-to-date and reliable account of the current level of industrial and business activity, has been a perennial endeavor of District Reserve Banks. Currently, only the Reserve Banks of Boston and Dallas are releasing production indexes on a regular basis for either the District or for a state in the District.—However, attempts have been made V ’’Electric Power - An Indicator of Industrial Activity,” New England Business Review, Federal Reserve Bank of Boston, February 1965, pp. 8-13; C. Howard Davis, "Improvement of Texas Industrial Production Index," Business Review, Federal Reserve Bank of Dallas, September 1968, pp. 3-7. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis -2- by several other Banks to develop similar series.- At the Federal Reserve Bank of Atlanta, an interest in the development of a District production index began in the early 1960’s when, as a part of a system-wide effort, the Bank began to collect statistics on kilowatt hours (KWH) of electricity sold to manufacturing by utilities. The project has been carried out under the general direction of Mr. Charles T. Taylor, Senior Vice President and Director of Research. Many of those on the Re search staff have participated in the project, including Messrs. Phil Web ster, Dale 0’Bannon, William Schleicher, and Richard Long. The greatest momentum for the project was provided by Mr. Long, my immediate predecessor, during the period between 1966 and 1968. Potential benefits that may be derived from the regional production index are substantial. First of all, the new District indexes will add another dimension to regional economic analysis by providing a reasonably reliable and up-to-date account of manufacturing activity at the regional level. Secondly, they will provide a statistical basis for analyzing and comparing interindustry as well as interregional manufacturing activity over a period of time, which will shed light on various forces that are relevant to the study of the growth process and cyclical phenomena observed 2/ — See Business Indexes Proposed for the Fifth District (mimeograph), un dated, Federal Reserve Bank of Richmond; "Toward an Index of Ninth District Industrial Production," Monthly Review, June 1966, Federal Reserve Bank of Minneapolis, pp. 3-7; "Electric Power Consumption in Manufacturing," Business Review, Federal Reserve Bank of Philadelphia, April 1961, pp. 24-26; "Electric Power as a Regional Economic Indicator," Economic Review, Federal Reserve Bank of Cleveland, September 1964, pp. 10-15; L. C. Anderson, "Value Added by Manu facture, Central Mississippi Valley Metro Areas, 1957-64," Review, Federal Re serve Bank of St. Louis, June 1964, pp. 5-10; "Electric Power Consumption - An Output Indicator in Milwaukee," Business Conditions, Federal Reserve Bank of Chicago, April 1962, pp. 5-11. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis -3- in a dynamic aspect of the regional economy. Thirdly, the indexes will satisfy, at least partially, the needs of private businesses and govern mental agencies for regional production data in their decision making. It is vitally important that planners have knowledge concerning changes in the productivity factors, as well as in the level of physical output of individ ual industries—including the ensuing changes in the relative structure of the regional industries. For instance, an increasing number of indi vidual companies study their own productivity estimate on a continuing basis in order to facilitate cost control and diversification planning, as well as for a variety of other reasons. The new District index will enable business to compare and analyze changes in their own productivity and level of output at the local level to those observed in the same industry of the District 3/ or national level.— Section II - Concept and Coverage The District manufacturing production index is designed to measure monthly changes in the level of physical output of District manufacturing. The output, which is measured in constant dollars to remove the effects of price changes over a period of time, is statistically estimated from two major factor inputs, _i.e^. , man-hours employed and KWH of electric power 3/ —' For methods measuring the productivity of individual companies, see John W. Kendrick and Daniel Creamer, Measuring Company Productivity, National Industrial Conference Board, New York, 1965. Additional discussions on the usefulness of the production index are found in Clayton Gehman and Cornelia Metheral, Industrial Production Measurement in the United States: Concepts, Uses, and Compilation Practices, Board of Governors of the Federal Reserve System, Washington, February 1964. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis -4- 4/ consumed, for 18 out of 21 two-digit SIC industries. The estimates for individual industries are combined to yield indexes for two major industrial groups (i.e., durables and nondurables) and total manufacturing. The index covers, in its entirety, all six states wholly or partially served by the Federal Reserve Bank of Atlanta and is based on about 90 percent coverage of the reported universe of man-hour and electricity consumption data ger mane to the six states’ industries. No attempt was made to incorporate actual output data into the index construction. The new index, as its title indicates, encompasses only the manufacturing sector and does not include utility and mining industries of the District states. While it is ideal to make a monthly measurement of production output by tabulating the actual quantity of goods produced in an industry, it is neither practical nor the most efficient method to accomplish the objective. First, there is a question whether many manufacturing concerns keep actual and reliable production data on a monthly basis. Even if all of them did, there still would be the formidable problem of collecting data directly from individual companies every month, even by sampling methods. Aggregating individual product data in a meaningful way would be an equally formidable problem because products are numerous and are not homogeneous in character. The theoretical production function provided the conceptual cornerstone 4/ For the time being, nroduction indexes for three industries (SIC 19, Ordnance and Accessories, SIC 38, Professional, Scientific, and Controlling Instruments? and SIC 39, Misscellaneous Manufacturing Industries) were not estimated primarily because of incompleteness in published man-hour and value added data and because of their relative insignificance in the overall manufacturing endeavor of the District. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis -5- in the development of the District’s production index.—More specifically, the new index has been developed on the assumption that the functional rela tionship between the rate of change in input factors and the rate of flow of physical output per time period can be statistically defined. Once the rela tionship is defined, the change in the level of output may be estimated by the changes in quantity of the input factors. The independent variables em ployed as the input factors of production are data on man-hours employed and industrial use of electric power; both are generally available at state levels for 2 digit SIC industries on a relatively current basis. Industrial output in constant dollars was approximated by deflating the value added data with the price index of the base year period. Since value added data are not available on a current basis, current outputs were estimated by extrapolating factor productivities along with the input variables. The out put estimate was then carried forward monthly until the census data became available, at which time output estimates made by the extrapolated factor productivities were adjusted to the new bench marks. Estimating procedures and the primary data employed in the derivation of the index are further elaborated in later sections of this note. — The input and output relationship in an aggregate production function encompassing the entire industry designated by the two digit SIC level is admittedly complex and poses difficult problems in the theoretical as well as empirical frame of reference. In this context, it must be emphasized that the theoretical production function provided only the conceptual guidance for the methodological frame of reference. For discussions on broad problems associated with the aggregate production function, see Franklin M. Fisher, ’’The Existence of Aggregate Production Function,’’ Econometrica, Vol. 37, 1969, pp. 553-577; and Robert M. Solow, ’’Some Recent Developments in the Theory of Production,” in Murray Brown, Ed., The Theory and Empirical Analysis of Pro duction, National Bureau of Economic Research, New York, 1967, pp. 25-53. See also, Franklin M. Fisher, "Embodied Technology and the Existence of Labour and Output Aggregated," Review of Economic Studies, Vol. 35, 1968, pp. 391-412. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis -6- The use of the productivity extrapolators for this purpose, which will be discussed further in Section V, may not be empirically valid under cer tain circumstances, and thus, the extrapolators may distort estimates of current outputs. 6/ However, experience seems to indicate that the produc tivity extrapolator generally yielded fairly reliable estimates in the past 7/ The use of the two factors of production as primary input variables is based on conceptual as well as practical considerations. Typically, the effects that changes in the quantity of the input factors have upon volume of output over a period of time are manifested through either ’’scale effect” or "technological effect," or through both. In other words, changes in physical output are affected not only by changes in the quantity of the in put factors but also by changes in the technological parameters of the pro duction function, which in turn are affected by changes in the factor pro ductivities and the marginal rates of technical substitution of the two factors. While it is almost a formidable task to isolate empirically the magnitude of output variations stemming from these two "effects" individually or jointly, it was felt that a combination of the two input variables in the ~ For instance, Hultgren and Kuh showed that changes in labor produc tivity tend to move in the same direction as changes in firms’ output during the business cycle period. See for instance, Thor Hultgren, Changes in Labor Cost During Cycles in Production and Business, National Bureau of Economic Research, New York, 1960, Chapter 2; and Edwin Kuh, Profits, Profits Markups, and Productivity, Joint Economic Committee, 86th Congress, Government Printing Office, 1960, pp. 61-111* Board of Governors of the Federal Reserve System, Industrial Production, 1959 Revision, Washington, 1960, pp. 22-24. —^Janies W. Knowles, "An Appraisal of Productivity Projections," Journal of American Statistical Association, June 1959, as quoted in John W. Kendrick, Productivity Trends in the United States, Princeton University Press, Prince ton, 1961, page 16. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis -7- same equation would reflect interaction effects that could not be shown through the use of either man-hour or KWH data alone. For instance, a more intensive use of capital is likely to be accompanied by increased use of electricity and a decrease in demand for labor. Over a period of time, how ever, the ratio between inputs of labor and KWH changes as a result of changes in the parameters of the production function, such as, changes in technology and work efficiency. Our experience indicates that the direction of change in the input ratio, as well as change in relative use of electric power to labor (as measured by KWH used per man-hour over a period of time), would not always show stable and predictable relationships. Furthermore, a number of recent studies indicated that the elasticity of factor substitu8/ tion for most U. S. manufacturing industries is close to unity. For this reason, in the construction of the new District index, it was assumed that the two input factors used had unitary elasticity of substitution. Except for the actual physical output data, which are not incorporated in the new District index, the District production index shares a basic affinity with the U. S. production index in its conceptual and methodological orientation. Like the U. S. production index, the new District index is — See for instance, Paul Zarembka, "On the Empirical Relevance of the CES Production Function," Review of Economics and Statistics, Vol. LII, Feb ruary 1970, pp. 47-53; C. A. Knox Lovell, "Biased Technical Change and Factor Shares in the U. S. Manufacturing," Quarterly Review of Economics and Busi ness , Vol. 9, Autumn 1969, pp. 17-33; and Phoebus J. Dhrymes and Paul Zarembka "Elasticities of Substitution for Two-Digit Manufacturing Industries: A Correction," Review of Economics and Statistics, Vol. LII, February 1970, pp. 115-117. For a discussion on recent developments in the CES production func tion see, Marc Nerlove, "Recent Empirical Studies of the CES and Related Pro duction Functions" in Brown, ibid., pp. 56-112, and articles presented in a symposium on CES production functions in Review of Economics and Statistics, Vol. 50, 1968, pp. 443-479. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis -8- designed on the basis of what is known as the Census ’’value added” concept. Value added by manufactures, as it is defined by the U. S. Bureau of Census, "is derived by subtracting the total cost of materials from the value of shipments and other receipts and adjusting the resulting amount by the net change in finished products and work-in-process inventories between the be- 9/ ginning and end of the year.’’- The value added by manufactures is generally considered to be the best empirical value measure of net output produced by individual industries. As such, it can be used to reflect an approximation of the net production of individual industries, and when aggregated for the entire District region, it can be regarded as reflecting an approximation of gross product originating in the District manufacturing sector.—The affinity of the concept will enhance the comparability of the U. S. data to the regional data, or vise versa, for various economic analysis. Section III - Estimating Equations and Procedures After considerable experimentation with various alternative approaches and formulas used by some Federal Reserve Banks and proposed by others, 11/ 9/ — U. S. Bureau of Census, Census of Manufactures 1963, Vol. I, page 22. —^For a detailed explanation on concepts employed in the construction of the U. S. production index, see Gehman and Metheral, ibid. , pp. 1-2. —^Various alternative approaches and formulas considered include: Pub lications cited in footnote 2 of this note, page 2; Technical Supplement to "Measuring New England’s Manufacturing Production" (mimeograph), and Edwin F. Estle and Jerilyn Fair, Technical Supplement to "Electric Power - An Indicator of Industrial Activity" (mimeograph), 1965, all of which were published by the Federal Reserve Bank of Boston; Richard Long, Measuring Regional Production, a proposal, undated, Federal Reserve Bank of Atlanta; Carl W. Hale, Methodology of the Texas Industrial Production Index, 1966, revision (mimeograph), July 1966, Federal Reserve Bank of Dallas. One of the more comprehensive studies on the development of a regional production on micro-approach may be found in T. Y. Shen, A Regional Production Index for New England (mimeograph), Federal Reserve Bank of Boston, Boston, 1960. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis -9- the following formulas and approaches were employed to estimate output for individual two-digit SIC industries in the District. Q,t = W -f it i O + W% gt i O hi (1) V Where A = L. it B - E Q’ it = wa 1 it * L . iy • E * iy (—)+Wu. 8i 1 &-) h. (2) V. Where A’ = L4it i-1966 L * • [1 + (u± • n)] i.1966 Vi.l966 B’ = E. it * * [1 + (v. ‘ n) ] E i.1966 Where Q = output index Wa = weight for man-hour index L = monthly man-hour input V = value added deflated by wholesale price index W^ = weight for KWH index E = KWH of electric power input L * annual average of man-hour input E = annual average of KWH input g = 1957-59 average of A series h = 1957-59 average of B series u = monthly increment factor of labor productivity determined by trend https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis -10- v = monthly increment factor of KWH productivity determined by trend i = industry t = month n = number of months counted consecutively by treating January 1967 to equal one y = year (NOTE: Subscripts, 1966, in A’ and B’ denote the year for which the latest Census data are available. As more current Census data become available, the subscript should be changed.) Equation (1) was used to obtain monthly production indexes of individual industries for the period between January 1960 and December 1966, while equa tion (2) was employed in deriving monthly indexes for January 1967 and there after. The two equations are basically the same except that A and B (i.e., out put estimates made by man-hour and KWH inputs independently) in equation (1) were obtained by the respective annual productivity factors derived from the census annual value added and man-hour data, whereas A’ and B’ in equation (2) were obtained by the productivity factors that were extrapolated largely on the basis of past trends. The productivity extrapolators, i.e., u-^ and v^, used are shown in Appendix A, Table 1. A couple of minor modifications were necessary in the actual operations series to a six-month or three-month moving average series for several indus tries before they were combined to yield an industry production index, and A B A’ B’ use of only the (—) , (—) , (—), or (-—) series because of input data problems g h g h for three particular industries. Types of specific variables used to derive the production index for an industry are shown in Appendix A, Table 2. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis -11- The estimation of the production index of individual industries for current month involves the following steps: (1) (2) (3) (4) estimation of output by man-hour input, i.e., A’ series estimation of output by KWH input, i.e., B’ series transformation of A’ and B’ series into an index ex pressed in terms of the 1957-59 average A’ summation of the two indexes, i.e., summation of (—) 8i B’ a and (—) with appropriate weights used, that is W . and b hi 1 W . These weights are explained in the next Section. The monthly production index derived from step 4 above is seasonally adjusted by the application of the Census X-ll seasonal adjustment program. Once the individual indexes are seasonally adjusted, no further seasonal adjustments were made in deriving the aggregate indexes of durable, nondur able, and total manufacturing. The seasonally adjusted aggregate indexes were obtained by summing the seasonally adjusted component indexes with industry weights. In formula: Q” t .................................... (3) Where Q" denotes an aggregate index * represents weights to individual indexes, which are expressed in fractions i and t represent industry and month, respectively W The industry weights used to obtain the aggregate indexes were derived from value added data of individual industries for 1963 to reflect the relative importance of an industry within the three specific groups. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis The industry -12- weights used are shown in Appendix A, Table 3. Section IV - Characteristics of the Estimating Equations The two basic formulas employed to derive the new District production index meet the tests of relative simplicity and economy, of consistency, and of uniformity. They are also, as pointed out earlier, compatible with the U. S. production indexes. First, as noted in the preceeding section, the estimation of monthly output for individual industries involves 4 relatively simple steps, which do not require extensive clerical work in collecting and processing primary in put data. Moreover, the operating procedure involved is uncomplicated so that overall cost necessary for computing and maintaining monthly indexes on a continuing basis will be minimal whether actual computational works are carried out by clerks or by computers. As long as the formulas and variables used yield reasonably meaningful empirical measurements of regional produc tion, the overall cost should be balanced and optimized in the light of po tential benefits derived from the use of the data. Secondly, the basic methodological framework is sufficiently consistent, not only with the theo retical production function but with the empirical relationship generally observed between certain key inputs and physical output. As will be dis cussed later, the formulas are capable of yielding estimated output indexes which are sufficiently reflective of changes in demand for input factors even when the practice of labor hoarding is prevalent. Finally, the estimating equations, as well as variables used, meet the test of uniformity in that in dexes for 18 individual industries were derived from a single basic formula, https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis -13- i.e., equation (2), with the use of the original regional data. All of the raw input variables used for the index derivation are original data applicable to the region, in contrast with data that can be derived from secondary sources, such as, deriving regional data by statistical decomposition of the national data. The use of original data as raw input has its own drawbacks, such as the occasional needs for estimating certain data at the state level, which were withheld in Census publications to preserve the confidentiality of individual firms. But, as compared with the use of secondary data derived from the national data, the use of the regional data permits ease in tracing the probable source of errors made not only in the computational stage but also those errors frequently made in the initial data collection and process ing stages. A specific advantage of relying exclusively on the original data is that this allows better control in processing the input variables and elim inates needs for revising the District indexes each time any part of the na tional data is revised. In addition to these general characteristics, there are two specific structural characteristics embodied in the estimating equations. The first of these characteristics is that the equations are designed to yield output estimates which produce the least statistical distortion when the estimates are indexed based on the 1957-59 average. As will be pointed out later, some of the District input variables used were partially estimated, and the esti mating equations were designed to keep the probable effects of the estimated variables at a minimum; because denominators "g" and ”h" (that is, the 195759 averages for "A" and "B" series) are by design, in fact, averages of value https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis -14- added for the 1957-59 period for individual industries. Thus, if man-hour inputs used for 1957, 1958, or 1959 were the variables estimated, the effects of the man-hour estimates will not affect the index series, since the man hour input will be cancelled out by the denominator used for the industry’s man-hour productivity for the year. This consideration is rather crucial in view of the fact that as we go back to the earlier years, the regional sta tistics available for many industries become pregressively more scarce. Moreover, we wanted to incorporate the industrial use of electric power, but data for electric power consumption by industry were not available prior to 1960 for the District states and prior to 1962 for the U. S. However, the cancelling feature of the estimating equations described above enabled us to arrive at the KWH index for individual industries on the basis of the appro priate 1957-59 average, as the yearly KWH data estimated for the 1957-59 pe riod were cancelled out by the same data used to obtain the annual KWH pro ductivity, leaving the value added data for the base year period intact. The second specific structural characteristic of the estimating equation is that they were designed to reflect composite effects on outputs arising from changes in the scale as well as the technology of production over a pe riod of time. It is true that the composite effects are statistically im pregnated in the productivity of the individual input factors, since the pro ductivity used for current measurements of output is derived by extrapolation. However, as an added built-in feature to make the index series more responsive to changes in the input mix as well as to periodic changes in relative impor tance of individual factors, the man-hour and KWH index series are derived https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis -15- independently, but are combined in weighted form to yield an industry index. (Weights used are shown in Appendix A, Table 4.) The weights used were based on labor and capital coefficients derived from the Cobb-Douglas produc tion functions computed for individual industries from 1963 man-hour and 12/ capital data. In addition to its conceptual merits for a long-run consideration, con current use of man-hour and KWH in the same formula enhances empirical reli ability of the index for the short run as well, because it increases the sensitivity of the index to reflect concurrent changes taking place in the production activity of industries. As discussed below, changes in KWH con sumption are a better barometer of changes in demand for energy in many in stances than changes in demand for labor reflected in man-hour data. Thus, use of two independent variables (i.e., man-hour and KWH indexes) in the same formula, in addition to making the output index more responsive to changes in demand for inputs of both factors, tend to minimize possible dis torting effects attributable to certain flaws residing in man-hour data used (Some of these flaws will be discussed in the next Section.) For one thing, monthly KWH data represent total electric energy consumed by industry during the entire month. Thus, with the exception of a certain fixed amount of — An estimation of capital stock for the District manufacturing indus tries has been made by this Bank as a separate staff research project which is still in progress. The principal methodology used for the estimation relied heavily on one developed by Gallaway. Cf. Lowell E. Gallaway, "Re gional Capital Estimates by Industry, 1954-57," Southern Economic Journal, Vol. XXIX, July 1962, pp. 21-25. Weights used for individual series were not revised for the entire time span of index coverage, but are scheduled to be reviewed and revised when the next Census of Manufactures becomes avail able, at which time all index series for 1967 and onward will be bench mark adjusted. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis -16- electric power used by industries for such overhead operations as lighting, space heating, or cooling, KWH consumed closely approximate the actual amount of electric energy used for production of firms’ output. Furthermore, KWH data readily reflects electric energy consumed by new establishments as well as discontinuation of power use by defunct firms. Section V - Data Sources and Limitations Annual value added and man-hour data by industry up to the years prior to 1967 were obtained from the Census of Manufactures for census years and from the Annual Survey of Manufactures for interim Census years. Monthly man-hour data for the years prior to 1968 were obtained from the Employment and Earning Statistics for the U. S., 1909-68, (U. S. Bureau of Labor Sta tistics, Bulletin No. 1312-6, 1968) and monthly man-hour data after 1968 were obtained from individual state labor departments in cooperation with the U. S. Bureau of Labor Statistics. Some of the data limitations which should be recognized for man-hour statistics are: First, they do not possess a high degree of sensitivity in reflecting changes in demand for labor because of a certain rigidity in down ward adjustment of work hours. For instance, during the beginning phase of business fluctuations, employers do not always lay off workers simply because demand for their products has slackened. This is particularly true when a business slowdown is expected to be brief in duration. Moreover, for certain processing industries in which production methods are highly automated and mechanized, such as chemical and petroleum industries, man-hour data are https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis -17- generally considered as a poor proxy for estimating physical output.-*- More importantly, monthly employment data, upon which man-hour data are based, do not represent a whole month but cover only a single survey week which includes the 12th day of the month. Also, man-hour data represent man-hour paid by employers rather than actual man-hours worked in plant for production This tends to distort actual amount of labor put into production, especially during those months when many workers are away from a plant on vacation. Finally, it should be emphasized that monthly man-hour data used were not de rived from well-controlled random samples. called "cutoff” sample method. They were derived by the so Under this method, tabulation of sample data are made until reports from a certain percentage of the sample firms have been received by the state labor departments. Consequently, the probability errors associated with sample procedures in data collection cannot be sta tistically determined and corrected. The KWH data that were utilized came from those collected and maintained by the Bank and the Board of Governors of the Federal Reserve System. While, as noted earlier, these data are fairly comprehensive and timely, they are not entirely free of structural defects. Wherever practical, efforts were made to negate potential effects of the data deficiencies. First, because of the cycle-billing method used by utility companies, 13/ — Experience of the Federal Reserve Bank of Dallas in the construction of the Texas production index shows that man-hour data cannot be relied on for chemical and petroleum industries, Minutes of the Workshop on Local Pro duction Indexes, (the conference was held at the Federal Reserve Bank of Cleveland on April 1964), Federal Reserve System, page 2. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis -18- monthly KWH data as reported may or may not coincide with the actual month for which the data represent. As an attempt to minimize this distortion, practically all of the KWH indexes were adjusted using either a six-month or a three-month moving average. Secondly, the consumption of electric power displays strong seasonal variations which are generally believed to be caused by widespread use of electricity for space heating and cooling. However, possible distortions arising from this source are also believed to have been substantially corrected by the seasonal adjustments applied B B’ 14/ to the KWH indexes, i.e., the (—) or G—) series. n• n. i l Thirdly, it should be recognized that for certain industries that rely heavily on energy other than electric power, KWH data may not have reliable empirical content as a major input factor. situation. No attempts were made to correct this particular 15/ There is an inherent difficulty in using regional data published in Census data. First, certain information was withheld from publication be cause of disclosure provisions. Those data withheld which were essential to the construction of the District index were estimated, while those that were relatively insignificant for our purpose were ignored. Secondly, state data published in the Annual Survey of Manufactures are subject to —^The KWH data used were not adjusted for working days due to a prac tical difficulty involved in ascertaining the correct working days for six different states. —/Since only KWH data and man-hour data are used as proxy measures of output, the relative weights assigned to the two individual input series may have been distorted for those industries that rely heavily on energy sources other than electric power. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis -19- sampling errors. Firms in the sample, as well as the sample size, vary from one year to another, and the Bureau of Census does not revise bench mark data for states once the data are published in the Annual Survey of Manufac tures . Thus, the District data compiled from the Annual Survey and certain computations derived from the data may not have the same accuracy as the similar data for the nation as a whole. As shown in Appendix A, Table 5, regression coefficients of annual man-hour productivity were lower for the District industries than for their national counterparts while the standard deviations were higher for the District industries than for the same indus tries in the U. S. However, complete bench mark revisions in the District index can be made when a comprehensive Census of Manufacture is made avail Despite incomplete nature of data published in Annual Survey of Manu able. factures , an annual bench mark revision may need to be made for interim Census years on the basis of the value added data published in the annual publication. Price data used to deflate value added figures were wholesale price in dexes applicable to two-digit or three-digit industry levels. ciencies in the use of price information should be pointed out. Several defi First, since no regional wholesale price data were available, the deflators used were the national data, compiled by the U. S. Bureau of Labor Statistics (BLS). Secondly, this deflation process differs from the so called ’’double deflation" method, generally used when separate price data for input factors and outputs are available. Under the double deflation method, values of in puts and outputs are deflated separately to obtain value added by appropriate https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis -20- price indexes applicable to either inputs or outputs. Thirdly, the BLS• uses the 1958 weights beginning in 1961 and the 1954 weights for 1958 through 1960. Since no adjustment could be made for the shifting in the BLS weight ing period, there is a slight possibility that some errors may have developed during our process of price deflation. If this were the case, the estimates of the productivities of man-hour and KWH which had been computed from the deflated value added might have been distorted. As shown in Section II of this note, the input productivity factor used for monthly indexes of January 1967 up to the present were extrapolated on the basis of historical trends of the respective productivity factors. It should be pointed out that productivity factors so calculated in many cases may not reflect an accurate picture of concomitant productivity changes in certain in dustries. For instance, they tend to underestimate current productivity for those industries where labor productivity has been rising rapidly, such as the machinery industry. On the other hand, they tend to overestimate the cur rent productivity for those industries whose productivities grow slowly or are not growing at all. Various empirical studies showed that changes occurring in labor productivity were quite sensitive to the business cycle, and changes in output per man-hour and those in the level of output in many industries 17/ were positively related. A couple of alternative approaches to overcome — A useful discussion on this point may be found in Paul A. David, ’’The Deflation of Value Added," Review of Economics and Statistics, Vol. 44, 1962, pp. 148-155. —^See on this point, Hultgren, ibid., Chapter 2 and Kuh, ibid. See also Thomas A. Wilson and Otto Eckstein, "Short-run Productivity Behavior in U. S. Manufacturing," Review of Economics and Statistics, Vol. 46, 1964, pp. 41-54, and T. Y. Shen, "Innovation, Diffusion, and Productivity Changes," Review of Economics and Statistics, Vol. 43, 1961, pp. 175-181. For a useful discussion on how man-hour productivity behaved for the postwar period and on the factor affected the productivity change, see Trend in Output Per Man-hour in the 'Pri vate Economy, 1909-1958, Bulletin No. 1249, U. S. Bureau of Labor Statistics, December 1959. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis -21- problems in using the productivity extrapolator have been suggested; however, data problems encountered at the regional level have precluded the applica- c , 18/ tion of the alternative approaches in the derivation of District indexes. In this respect, for certain industries that are vulnerable to cyclical swings, such as the primary metals industry, use of the productivity extrapola tor as the current productivity factor may have a strong tendency to distort the true picture of productivity changes during cyclical fluctuations. Another potential source of distortion that may have affected the size of the productivity extrapolators was the application of a single extrapolator to broad industrial groupings designated by two-digit SIC. There is no doubt that the empirical reliability of the index would have been enhanced if the productivity extrapolators had been computed and applied to a three-digit SIC industry basis. Another limitation inherent in the new District indexes is that they are incapable of reflecting inventory change and shipment situation. Therefore, if it is assumed that no stable functional relationship existed between produc tion and shipment over a long period of time, the validity of the new District index is weakened, particularly, the usefulness of the indexes as empirical measurements to reflect business cycle phenomena. Section VI - Empirical Validity of District Production Index Discussion will now be focused on the attempt made to assess the empirical — Hultgren suggested the use of man-hour and payroll indexes divided by the index of quantity of output sold, and Shen suggested the estimation of value added and productivity on the basis of the estimation of cross section parameters. See Thor Hultgren, Cost, Prices, and Profits ; Their Cycle Rela tions , National Bureau of Economic Research, New York, 1965, pp. 13-36, and T. Y. Shen, ibid. , (A Regional Production Index for New England), page 6. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis -22- reliability of District production index. Since data on actual outputs by District industries are not available, it is impossible to apply direct tests on the District indexes which are, in fact, the summary measures derived from the use of the estimating formulas and statistical procedures. Consequently, only indirect tests can be made to determine whether the behavioral patterns of computed District indexes have reasonably reliable empirical contents as in dividual component series or as an aggregate series, such as the total manufac turing index. Two indirect methods were employed in the present investigation. The first method relied on a detailed analysis of graphical, behavioral patterns of the District’s individual industry index series. The individual industry series were first examined for their seasonal patterns, general trend behavior, and obvious erratic movements. Then, they were compared with the comparable TJ. S. production index series to study their relative behavioral patterns. More specifically, the behavior of each District index and its U. S. counterpart is analyzed to detect conformity, or lack of it, between them in the timing of the series’ turning points, as well as in the direction and slope of the series’ movements. In general, except for a few isolated incidences where divergences observed between District and U. S. indexes series could not be satisfactorily accounted for, the District production indexes, both as in dividual components and as an aggregate series, appeared to be reasonably reli able summary measures which reflect changes in the level of physical outputs by individual industries. The other method employed as the indirect test was to measure quantita tively the relative performance of the District production indexes. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis One -23- possible way of accomplishing this test is by applying statistical measures to joint distributions of two sample universes that are delineated by common denominators. The testing procedure that was devised, related the distri bution of annual production index ratios for the District and U. S. to the distribution of annual employment index ratios for the District and U. S. for each industry. In order to standardize the variables, the employment data were indexed in relation to the 1957-59 average. District variables for each given year were then expressed in relation to the value of the U. S. variables Consequently, since the ratio variables used for testing were ones jointly determined by the relevant District and U. S. variables, they will reflect changes observed both within and between time periods. As will be seen shortly, this simple procedure permits the formulation and testing of an hypothesis which is more meaningful than mere descriptive measures, such as means and standard deviations. One important assumption underlying the testing procedure is that for each industry in any given year, the variances observed between District and U. S. employment are equal to the variances observed between District and U. S production indexes. That is, for a given industry, the parameters for the production functions of the District and the U. S. are the same. Another im portant assumption is that all variables used in computing the annual ratios for the two sample universes are accurate and empirically reliable, except for the District production indexes. If these two assumptions hold true, the variances observed in the District production index in relation to the U. S. index will be equal to the variances observed in the District employment index https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis -24- in relation to the U. S. index for the same industry. To illustrate the procedures used, two sets of ratio variables were ob tained individually for nine major industries in the District. The combined value added for these industries accounts for almost two-thirds of the total value added for the District’s entire manufacturing. covered a nine-year period from 1960 through 1968. Each ratio variable The first set of ratio variables was computed by dividing the annual District production index for an industry by the U. S. production index for the same industry. The second set of ratio variables was obtained by dividing the annual District employ ment index for an industry by the U. S. employment index for the same industry. Then, arithmetic means and standard deviations were computed for each set, and they were compared with each other on an industry basis. was followed for total manufacturing. The same procedure Results of the computations are shown in Appendix A, Table 6. A close examination of the table indicates that generally the sample means of production indexes are very similar to those of the employment indexes. In order to tests the statistical significance of differences observed between the two sample means, tests were made on the hypothesis that u^ = u^? that is, there is no difference between the two means. On the basis of this testing, the hypothesis for all of the nine selected industries, except three (i.e., textiles, lumber and wood, and paper), was accepted at the 5-percent level of significance. At this point, it should be emphasized that the rejection of the hypothesis for three industries does not necessarily indicate flaws in their production https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis -25- indexes. When considering the assumption underlying the test (i.e., there is no difference in the parameters of the production functions between the District and U. S. for the same industry), the rejection of the hypothesis for certain industries was not unexpected. In this respect, the rejection of the hypothesis for these three industries actually enhances the empirical validity of their District indexes; because in these industries, the Dis trict has the relative comparative advantage over other regions in its inter regional trade. As such, productivity of these industries in the District has usually been higher than that of its U. S. counterparts. For instance, in 1966, the value of shipments per man-hour for the District’s paper indus try was $22.36, as compared with $18.98 for the U. S. paper industry as a whole/ When considering that errors can be accumulated in the individual Dis trict production indexes under the methodology used in the index derivation (i.e., continuous application of monthly productivity extrapolators used in the District indexes), and when considering the potential problems presented by various limitations of the regional data employed, the results of the sta tistical testing seem to validate the empirical contents of the new District production indexes even more than the investigator had hoped. 19/ — See C. S. Pyun, "The Southeast’s Booming Paper Industry," Monthly Review, Federal Reserve Bank of Atlanta, September 1969, page 111. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis APPENDIX A, Table 1. PRODUCTIVITY EXTRAPOLATORS KWH Man-hour Monthly Increment Factor Productivity 1966 Monthly Increment Factor Industry Productivity 1966 Food (20) 257.34 .0020295 .804 -.0014057 Tobacco (21) 213.26 .0021665 3.260 -.0074888 Textiles (22) 202.37 .0046460 .320 .0018950 Apparel (23) 123.95 .0020077 2.970 -.0051686 Lumber and Wood (24) 127.71 .0049868 .690 -.0026000 Furniture and Fixtures (25) 165.45 .0016378 1.440 -.0065684 Paper (26) 400.08 .0024894 .127 .0001890 Printing and Publishing (27) 254.87 .0013271 2.080 -.0064099 Chemicals (28) 551.42 .0058098 .144 .0003350 .276 -.0002200 .070 .0046950 Petroleum (29) Rubber (30) 606.45 .0052336 Leather (31) 183.15 .0012136 Stone, Clay, and Glass (32) 251.33 .0014557 Primary Metals (33) 367.84 .0036993 Fabricated Metals (34) 241.25 .0016778 Non-Electrical Machinery (35) 257.73 .0006519 1.580 -.0016623 Electrical Machinery (36) 399.50 .0064015 .730 .0045170 Transportation Equipment (37) 293.18 .0027751 1.530 .0050990 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis -27- APPENDIX A Table 2. INDUSTRY INDEX DERIVATION Indus try Component and Type of Variable Used Food (20) Man-hour and KITH** Tobacco (21) Man-hour* only Textiles (22) Man-hour and KWH** Apparel (23) Man-hour and KWH** Lumber and Wood (24) Man-hour and KWH** Furniture and Fixtures (25) Man-hour and KWH** Paper (26) Man-hour and KWH** Printing and Publishing (27) Man-hour and KWH** Chemicals (28) Man-hour and KWH** Petroleum (29) KWH* only Rubber (30) Man-hour and KWH** Leather (31) Man-hour* only Stone, Clay, and Glass (32) Man-hour only Primary Metals (33) Man-hour and KWH* Fabricated Metals (34) Man-hour* only Nonelectrical Machinery (35) Man-hour and KWH Electrical Machinery (36) Man-hour and KWH Transportation Equipment (37) Man-hour* and KWH NOTE: Components with one asterisk (*) means that they were adjusted on a three-month moving average and components with two asterisks (**) rep resent those series adjusted on a six-month moving average. Com ponents with no asterisk means that they were used in their original form with no moving average applied. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis -28- APPENDIX A Table 3. VALUE ADDED BY MANUFACTURE, 1963 District States Value Added ($000) Industry Total Manufacturing Percent Distribution 13,871,153 100.00 1,993,253 14.37 66,703 0.48 1,070,613 7.72 Apparel (23) 952,616 6.87 Lumber and Wood (24) 571,356 4.12 Furniture and Fixtures (25) 285,504 2.06 1,122,583 8.09 516,991 3.73 Chemicals (28) 2,149,584 15.50 Petroleum (29) 330,999 2.38 Rubber (30) 291,133 2.10 Leather (31) 163,297 1.18 Stone, Clay, and Glass (32) 672,145 4.84 1,007,192 7.26 Fabricated Metals (34) 652,016 4.70 Nonelectrical Machinery (35) 422,151 3.04 Electrical Machinery (36) 546,448 3.94 1,056,569 7.62 Food (20) Tobacco (21) Textiles (22) Paper (26) Printing and Publishing (27) Primary Metals (33) Transportation Equipment (37) Source: U. S. Bureau of Census, Census of Manufactures, 1963. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis -29- APPENDIX A Table 4. FACTOR WEIGHTS, 1963 Industry Man-hour Weight KWH Weight Food (20) .2132 .7868 Tobacco (21) .2900* .7100* Textiles (22) .4682 .5318 Apparel (23) .4740 .5260 Lumber and Wood (24) .4763 .5237 Furniture and Fixtures (25) .4323 .5677 Paper (26) .3095 .6905 Printing and Publishing (27) .3202 .6798 Chemicals (28) .1751 .8249 Petroleum (29) .1867* .8133* Rubber (30) .3179 .6821 Leather (31) .4156* .5844* Stone, Clay, and Glass (32) .2904* .7096* Primary Metals (33) .3189 .6811 Fabricated Metals (34) .3747* .6253* Nonelectrical Machinery (35) .3685 .6315 Electrical Machinery (36) .2673 .7327 Transportation Equipment (37) .3603 .6397 *These weights were not used in computing production indexes for the indicated industries because only a single input series (i. e., either man-hour or KWH input series) was used in the index derivation for these industries. See Appendix A, Table 2, page 27 from the specific input series used. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis LINEAR REGRESSION OF ANNUAL MAN-HOUR PRODUCTIVITY, 1957-65 APPENDIX A, Table 5. (y = a + bx Industry Food (20) Tobacco (21) Textiles (22) Apparel (23) Lumber and Wood (24) Furniture and Fixtures (25) Paper (26) Printing and Publishing (27) Chemicals (28) Petroleum (29) Rubber (30) Leather (31) Stone, Clay, and Glass (32) Primary Metals (33) Fabricated Metals (34) Machinery (35) Electrical Machinery (36) Transportation Equipment (37) NOTE: y = annual man-hour productivity; x = n; xo = 1956) Regression Coefficient District Coefficient of Correlation Standard Error of Estimate 7.73 2.92 8.93 4.72 4.84 4.07 13.39 3.82 25.00 29.53 13.27 1.32 11.52 13.02 4.63 14.19 11.10 12.35 .952 .256 .985 .889 .877 .806 .958 .728 .940 .768 .740 .307 .879 .851 .921 .890 .930 .846 6.426 28.455 4.024 6.278 6.861 7.714 10.398 9.297 23.501 63.498 31.152 10.518 16.143 20.739 5.061 18.759 11.292 20.079 Regression Coefficient U. S. Coefficient of Correlation Standard Error of Estimate 11.02 20.94 7.84 4.27 6.07 3.60 8.52 6.63 23.77 34.30 9.87 2.22 9.46 8.82 5.56 9.41 15.48 15.94 .980 .990 .990 .914 .968 .939 .989 .987 .982 .967 .989 .761 .938 .953 .971 .956 .977 .990 5.787 7.832 2.872 4.877 4.038 3.413 3.242 2.810 11.688 23.207 3.764 4.896 9.045 7.226 3.558 7.454 8.767 5.779 Value of regression coefficients for both the District and the U. S. are large because annual man-hour produc tivity data regressed were obtained by using annual average man-hour data. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis APPENDIX A, Table 6 Industry RELATIVE PERFORMANCE OF DISTRICT PRODUCTION INDEXES FOR SELECTED INDUSTRIES Ratio of District Production Index to U. S. Production Index Standard Mean Deviation Ratio of District Employment Index to U. S. .Employment Index Standard Mean Deviation Computed t Value* Food (20) 1.0763 .0305 1.0920 .0397 .8870 Textiles (22) 1.2122 .1111 1.0359 .0194 4.4185 Apparel (23) 1.3242 .1707 1.2980 .1326 .3429 Lumber and Wood (24) 1.0990 .0959 .9852 .0145 3.3178 Paper (26) 1.0764 .0149 .9834 .0260 8.7736 Chemicals (28) 1.0430 .0422 1.0279 .0379 .7550 Stone, Clay, and Glass (32) 1.0561 .1389 1.0992 .0551 .8163 Fabricated Metals (34) 1.1551 .0971 1.1610 .0942 .1234 Transportation Equipment (37) 1.2984 .2945 1.3429 .2118 .3468 Total Manufacturing 1.1403 .0880 1.1108 .0578 .7930 * - t with 16 degrees of freedom at the .05 level is 2.12. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis APPENDIX B 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 PRODUCTION INDEX SIXTH FEDERAL RESERVE DISTRICT STATES SIC 20 - FOOD AND KINDRED PRODUCTS (Seasonally Adjusted, 1957-59=100) Jan. Feb. Mar. Apr. May 111.0 112.5 122.3 128.3 136.7 140.3 142.5 143.9 149.0 111.3 114.3 122.3 128.9 137.4 141.4 143.0 144.9 150.3 112.5 115.6 122.7 128.1 138.1 142.8 145.1 144.9 151.0 112.7 116.1 123.2 128.9 139.1 141.1 146.3 145.2 151.6 114.3 117.9 122.4 129.0 138.6 141.2 146.9 147.0 152.7 June July Aug. Sept. Oct. Nov. Dec. 110.7 115.3 119.8 122.0 130.0 138.0 140.5 150.2 149.6 155.2 112.6 114.3 121.3 121.0 131.5 137.0 140.8 150.1 149.8 158.3 111.9 113.9 120.2 121.6 133.2 137.0 140.7 149.8 151.3 158.5 111.8 113.5 120.8 124.4 133.7 136.2 140.9 149.6 152.1 158.8 111.0 113.1 121.9 125.6 133.2 137.2 140.8 148.4 153.1 160.5 110.8 112.7 122.2 126.6 135.7 138.1 141.5 147.4 153.2 161.0 111.8 113.2 121.6 129.0 137.8 139.0 142.1 146.9 153.8 161.7 i w ro I SIC 21 - TOBACCO MANUFACTURES (Seasonally Adjusted., 1957=59=4-00) 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Jan. Feb. Mar. Apr. May June July Aus- Sept. Oct. Nov. Dec. 90.5 86.1 88.2 85.1 85.5 83.1 84.8 73.8 73.5 89.9 88.2 85.3 84.9 89.2 83.5 84.6 83.3 83.2 74.7 97.5 87.0 85.0 82.4 90.9 81.6 86.5 82.9 80.1 74.8 98.0 86.3 83.6 82.4 94.4 80.8 86.1 84.2 79.8 74.7 98.8 88.0 79.9 82.4 92.4 81.8 85.6 86.4 80.4 75.2 97.5 90.6 79.8 81.8 91.4 81.6 86.5 82.5 80.8 75.3 97.2 92.6 80.9 84.7 88.3 82.7 85.8 82.3 80.6 75.0 99.6 94.8 83.0 80.5 86.1 82.8 86.0 83.0 78.7 75.1 101.9 94.8 83.3 81.6 85.9 83.1 84.6 87.0 78.7 75.4 104.5 93.7 84.2 82.0 85.5 82.5 85.0 87.3 79.0 76.0 99.3 90.3 86.4 82.1 86.5 82.1 85.3 76.1 78.0 75.2 99.9 88.0 89.2 84.2 86.5 81.9 85.9 76.0 76.7 74.9 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis SIC 22 - TEXTILE MILL PRODUCTS (Seasonally Adjusted, 1957-59=100) 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. 113.8 127.7 125.8 136.9 159.3 182.2 190.7 199.4 216.3 113.4 130.2 124.7 139.2 161.7 182.2 188.1 202.6 216.1 114.2 130.9 124.5 141.8 163.7 183.2 186.8 205.0 218.7 115.0 130.6 125.6 144.3 166.1 184.1 185.5 203.7 219.7 116.5 130.6 125.8 142.1 167.9 185.7 187.1 206.1 222.8 115.7 116.4 130.3 126.5 149.9 170.3 184.5 187.8 208.8 225.1 115.4 119.6 130.1 127.5 152.3 171.8 188.5 187.8 210.4 228.4 113.4 121.2 130.5 128.0 150.9 174.0 189.4 188.5 212.3 229.8 112.1 123.1 129.3 129.3 150.3 174.7 190.9 190.8 212.9 231.4 110.7 124.2 128.4 131.2 154.4 176.5 190.4 193.0 213.6 229.4 110.8 125.0 128.3 132.4 155.6 178.6 190.2 195.0 215.3 229.3 110.5 126.2 127.3 134.0 156.9 180.6 190.3 197.4 215.9 228.9 SIC 23 - APPAREL AND OTHER FINISHED PRODUCTS (Seasonally Adjusted, 1957-59=100) 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Jan. Feb. Mar. APr- May June July Aug. Sept. Oct. Nov. Dec. 118.9 128.4 153.1 182.3 196.0 209.7 216.7 216.8 240.5 122.8 136.6 156.4 182.8 192.9 208.9 216.1 225.2 243.0 119.1 138.4 163.1 182.3 194.0 208.2 216.9 230.1 244.6 119.6 137.6 167.7 180.8 194.7 210.5 219.3 230.6 244.1 118.8 138.0 174.6 178.8 195.5 204.3 221.0 233.8 244.0 114.8 119.7 139.5 179.4 180.5 197.3 206.9 227.1 239.3 249.9 115.2 121.9 140.7 180.8 182.9 197.4 206.6 223.4 237.1 250.6 115.1 124.4 142.0 182.7 184.2 202.1 209.8 219.5 237.7 248.4 115.9 126.6 144.8 183.1 184.2 204.6 211.6 219.3 238.5 254.1 114.8 128.4 146.6 182.3 186.6 206.9 213.2 218.2 239.2 254.0 115.1 131.1 147.9 182.6 188.9 207.7 213.2 219.1 240.6 257.2 114.0 133.3 148.6 183.3 189.9 208.8 215.4 219.8 240.9 255.8 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis SIC 24 - LUMBER AND WOOD PRODUCTS (Seasonally Adjusted, 1957-59=100) 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Jan. Feb. Mar. Apr. May June July Aug- Sept. Oct. Nov. Dec 95.5 97.6 114.2 126.0 128.9 137.2 144.2 133.5 159.0 94.0 103.7 116.0 128.3 126.7 137.1 140.6 142.7 161.8 93.3 104.2 117.8 128.1 128.3 137.6 139.3 144.0 156.1 93.8 104.5 120.2 127.4 129.5 139.2 137.4 145.4 163.1 95.2 105.9 122.1 127.7 129.5 140.8 134.9 149.3 163.5 100.6 97.2 104.3 125.3 128.2 128.5 141.3 134.3 153.2 167.2 100.8 98.2 105.4 126.1 128.3 130.1 141.9 130.6 156.7 166.6 99.0 100.5 105.1 127.7 127.3 131.3 143.2 133.8 156.9 168.0 98.7 101.7 107.3 127.9 125.6 130.8 144.6 135.2 156.9 167.8 96.8 101.8 108.0 128.9 126.0 133.4 144.2 135.2 156.4 167.5 96.7 101.9 108.9 129.2 128.7 134.7 143.4 135.2 157.2 166.6 94. 101.1 108.1 128. 127.1 136.1 144.1 136.1 157. 166 • SIC 25 - FURNITURE AND FIXTURES (Seasonally Adjusted, 1957-59=100) 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Jan. Feb. Mar. Apr. May June July Au.g,- Sept. Oct. Nov. Dec. 101.4 105.8 126.3 145.8 161.1 178.3 184.1 179.1 197.2 99.4 112.5 127.7 146.7 162.6 179.0 182.9 182.9 198.1 98.1 114.5 129.6 146.2 165.1 179.5 182.1 185.2 198.3 97.9 115.5 131.2 146.8 167.1 180.4 181.0 184.6 200.6 97.1 117.7 133.0 147.3 169.1 179.4 181.6 189.2 196.6 103.1 97.7 120.3 135.0 146.8 170.0 181.4 181.7 192.6 197.7 104.6 100.7 121.5 136.6 146.4 172.2 181.9 183.5 193.0 192.7 105.3 102.7 122.5 138.7 148.6 173.4 183.5 179.4 194.1 195.6 104.7 105.0 124.6 139.7 150.6 174.0 184.2 178.9 194.3 194.4 104.7 106.0 124.5 141.6 153.5 175.1 184.8 177.3 194.9 192.4 102.9 108.0 125.1 142.6 154.9 177.0 185.2 178.7 194.6 190.3 102.0 109.9 124.6 142.9 157.8 178.4 183.8 181.0 196.6 185.9 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis SIC 24 - LUMBER AND WOOD PRODUCTS (Seasonally Adjusted, 1957-59=100) 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. 95.5 97.6 114.2 126.0 128.9 137.2 144.2 133.5 159.0 94.0 103.7 116.0 128.3 126.7 137.1 140.6 142.7 161.8 93.3 104.2 117.8 128.1 128.3 137.6 139.3 144.0 156.1 93.8 104.5 120.2 127.4 129.5 139.2 137.4 145.4 163.1 95.2 105.9 122.1 127.7 129.5 140.8 134.9 149.3 163.5 100.6 97.2 104.3 125.3 128.2 128.5 141.3 134.3 153.2 167.2 100.8 98.2 105.4 126.1 128.3 130.1 141.9 130.6 156.7 166.6 99.0 100.5 105.1 127.7 127.3 131.3 143.2 133.8 156.9 168.0 98.7 101.7 107.3 127.9 125.6 130.8 144.6 135.2 156.9 167.8 96.8 101.8 108.0 128.9 126.0 133.4 144.2 135.2 156.4 167.5 96.7 101.9 108.9 129.2 128.7 134.7 143.4 135.2 157.2 166.6 94.2 101.0 108.0 128.6 127.0 136.0 144.0 136.0 157.3 16$. 3 SIC 25 - FURNITURE AND FIXTURES (Seasonally Adjusted, 1957-59=100) 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. 101.4 105.8 126.3 145.8 161.1 178.3 184.1 179.1 197.2 99.4 112.5 127.7 146.7 162.6 179.0 182.9 182.9 198.1 98.1 114.5 129.6 146.2 165.1 179.5 182.1 185.2 198.3 97.9 115.5 131.2 146.8 167.1 180.4 181.0 184.6 200.6 97.1 117.7 133.0 147.3 169.1 179.4 181.6 189.2 196.6 103.1 97.7 120.3 135.0 146.8 170.0 181.4 181.7 192.6 197.7 104.6 100.7 121.5 136.6 146.4 172.2 181.9 183.5 193.0 192.7 105.3 102.7 122.5 138.7 148.6 173.4 183.5 179.4 194.1 195.6 104.7 105.0 124.6 139.7 150.6 174.0 184.2 178.9 194.3 194.4 104.7 106.0 124.5 141.6 153.5 175.1 184.8 177.3 194.9 192.4 102.9 108.0 125.1 142.6 154.9 177.0 185.2 178.7 194.6 190.3 102.0 109.9 124.6 142.9 157.8 178.4 183.8 181.0 196.6 185.9 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis SIC 26 - PAPER AND ALLIED PRODUCTS (Seasonally Adjusted, 1957-59=100) 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. 120.8 124.5 128.9 130.1 144.2 159.4 172.5 175.5 182.9 119.5 125.0 129.6 132.5 145.0 160.8 172.9 176.1 185.1 120.4 125.3 128.8 133.8 146.1 163.7 173.8 175.8 186.0 121.3 127.4 126.2 135.8 146.9 167.5 171.6 176.7 189.8 122.0 127.8 125.5 137.3 147.9 168.1 170.8 177.5 193.6 119.6 122.8 129.4 123.8 138.3 149.2 170.1 171.2 176.0 194.8 119.2 123.6 129.3 123.8 139.7 149.8 172.0 171.6 177.2 196.7 120.1 124.8 130.7 124.0 140.0 150.5 172.1 172.0 178.3 197.4 119.6 125.0 131.1 121.1 141.1 152.2 172.7 173.1 178.3 199.5 119.9 125.4 131.5 125.5 141.4 153.2 173.7 173.4 178.4 200.6 118.9 125.9 131.8 126.2 142.0 154.9 174.7 174.2 179.5 200.6 118.4 126.2 132.6 126.6 143.1 156.9 172.9 174.9 181.0 202.9 SIC 27 - PRINTING, PUBLISHING, AND ALLIED INDUSTRIES (Seasonally Adjusted, 1957-59=100) 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. 114.2 113.2 112.0 125.8 131.4 149.8 163.2 163.2 165.5 113.0 114.5 111.6 125.8 134.1 150.9 163.8 163.8 166.3 113.3 114.1 111.1 125.9 135.2 153.4 164.5 164.9 165.9 109.7 114.1 114.0 126.0 137.0 152.8 165.2 165.3 165.0 107.3 113.7 116.5 124.6 138.6 153.4 166.3 165.7 163.9 111.7 107.6 113.7 117.8 125.6 140.3 155.0 164.9 167.2 165.6 113.2 107.6 114.9 118.6 126.9 140.7 156.5 164.9 166.1 166.7 113.6 108.4 116.1 119.8 127.8 141.7 157.6 163.3 167.4 168.0 113.7 109.0 115.2 121.9 128.1 143.7 158.2 161.9 167.3 168.5 115.4 110.4 114.3 122.3 128.9 145.8 160.3 161.9 166.9 168.8 116.2 111.4 113.3 123.4 130.0 147.0 162.0 161.5 167.1 170.5 115.0 114.2 112.7 124.2 131.2 148.0 162.8 162.5 167.0 170.6 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis SIC 28 - CHEMICALS AND ALLIED PRODUCTS (Seasonally Adjusted, 1957-59=100) 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. 121.1 130.0 144.4 168.4 168.9 194.9 214.1 230.7 249.8 123.2 128.0 145.1 169.7 173.6 196.0 217.0 233.3 251.0 112.4 124.0 125.2 148.9 169.4 178.0 195.5 219.5 234.8 251.4 114.8 124.9 127.4 151.0 171.3 182.1 198.7 219.2 237.3 254.7 113.0 126.6 129.1 152.8 170.7 182.0 201.8 219.8 237.0 256.0 111.9 128.6 130.0 151.8 171.6 184.3 203.4 222.6 237.8 254.6 110.4 126.7 132.9 154.1 169.8 185.9 205.3 226.5 238.0 255.8 111.7 124.9 134.9 155.0 169.7 188.5 207.6 228.8 239.5 255.7 112.4 122.8 138.3 155.7 169.9 189.0 209.1 229.3 245.3 261.0 116.3 124.8 141.8 157.2 169.7 190.8 208.9 230.6 249.9 263.4 117.1 127.1 143.6 162.1 168.4 191.2 209.7 232.6 252.5 265.0 119.5 131.8 144.0 166.2 166.7 193.1 209.2 231.8 250.7 261.2 SIC 29 - PETROLEUM REFINING AND RELATED INDUSTRIES (Seasonally Adjusted, 1957-59=100) 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Jan. Feb. Mar. Apr. May June July Aug^ Sept. Oct. Nov. Dec. 106.0 103.6 104.6 125.3 125.4 135.4 138.3 151.1 147.1 125.0 109.9 107.7 119.4 125.1 139.7 135.5 153.0 157.9 108.4 139.3 112.5 109.3 111.0 122.6 141.4 129.9 152.9 175.3 114.7 146.8 115.7 111.4 115.1 123.2 144.4 136.3 152.4 176.1 113.3 134.7 116.4 112.9 116.8 122.7 143.0 141.2 151.0 178.1 102.0 117.5 116.3 113.9 120.3 122.9 140.9 152.8 151.3 174.2 96.4 100.8 116.3 116.0 121.9 125.8 140.2 155.0 148.6 177.9 90.8 97.7 118.6 116.3 124.5 129.6 139.3 146.5 144.6 171.6 93.8 98.6 112.8 119.6 126.3 128.8 142.7 135.2 145.6 165.5 89.6 98.7 107.4 126.0 125.5 127.7 143.5 131.7 147.7 161.7 89.2 98.1 100.5 131.4 125.3 126.1 145.5 145.3 146.9 159.8 90.2 99.5 102.5 135.3 126.2 130.5 144.8 155.4 140.1 159.7 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis SIC 30 - RUBBER AND MISCELLANEOUS PLASTIC PRODUCTS (Seasonally Adjusted, 1957-59=100) 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Jan. Feb. Mar. Apr. Mav June July Aug. Sept. Oct. Nov. Dec. 112.6 131.8 139.3 159.4 179.8 229.4 249.4 273.2 318.0 115.0 132.1 146.7 156.6 186.7 232.2 249.3 274.6 326.5 116.2 131.5 151.7 157.7 192.7 233.3 246.0 281.0 326.3 118.5 130.5 155.1 159.2 199.9 236.8 247.1 283.8 336.8 122.5 130.5 154.5 161.5 208.7 237.7 227.8 288.6 340.5 116.3 125.8 131.2 156.7 162.1 220.1 237.8 234.9 298.1 348.4 117.5 127.8 131.6 164.5 163.4 218.8 240.7 231.3 295.6 354.1 116.0 128.1 131.4 154.2 171.3 223.9 239.5 254.5 298.2 351.4 114.8 129.8 134.0 156.9 175.5 222.4 241.8 257.6 301.8 359.2 113.8 129.9 135.2 159.8 173.5 223.9 243.0 260.8 305.2 363.8 112.6 131.4 139.0 158.2 174.8 226.2 244.7 265.1 312.6 369.6 110.3 131.8 140.7 159.6 174.3 230.1 243.8 266.0 318.4 379.7 SIC 31 - LEATHER AND LEATHER PRODUCTS (Seasonally Adjusted, 1957-59=100) 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. 98.0 105.2 108.7 128.4 139.5 146.8 155.5 160.0 167.1 99.2 105.3 109.3 128.1 141.4 150.7 151.7 156.7 162.4 101.6 100.3 105.0 111.5 128.9 140.5 153.4 154.9 158.2 162.0 101.1 100.1 104.7 114.5 128.2 139.1 154.9 154.5 161.8 163.2 99.0 99.5 104.9 118.4 131.3 136.7 155.0 155.4 163.6 163.0 98.8 98.0 103.8 123.0 134.1 133.4 156.6 154.4 165.6 160.3 101.1 96.9 104.2 124.8 136.6 134.4 158.5 153.7 165.5 153.6 102.5 97.1 104.0 127.8 137.3 136.6 159.8 153.3 164.5 148.6 101.3 98.9 105.5 125.7 137.0 141.4 158.8 153.9 162.6 145.8 99.1 101.2 106.1 126.1 136.8 144.0 157.4 155.7 163.0 147.3 98.5 103.2 107.3 124.6 136.5 144.2 157.1 158.4 164.3 151.6 98.6 104.5 107.3 127.2 138.7 145.1 155.7 161.9 167.7 159.4 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis SIC 32 - STONE, CLAY, GLASS, AND CONCRETE PRODUCTS (Seasonally Adjusted, 1957-59=100) 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Jan. Feb. Mar. Apr. May June July A«g- Sept. Oct. Nov. Dec. 120.9 120.8 118.5 143.6 146.2 164.1 163.5 149.2 155.1 166.5 117.3 118.8 133.3 140.7 153.7 164.5 160.2 148.7 156.0 174.0 110.6 115.9 136.9 144.7 154.3 163.7 159.7 150.7 153.8 167.9 121.2 115.2 136.7 146.5 154.3 165.7 160.3 150.0 156.0 163.6 114.9 115.1 138.0 148.8 154.6 167.3 154.3 149.1 159.0 164.0 115.7 115.6 140.3 150.2 155.0 166.4 152.8 150.7 163.0 166.6 115.3 117.8 141.3 151.3 154.2 168.7 152.1 150.5 162.2 169.5 115.4 123.0 142.7 151.7 155.0 167.8 151.7 152.7 161.5 167.4 112.7 123.8 143.9 152.9 152.5 165.1 151.9 152.9 163.3 168.0 118.3 119.1 144.4 154.0 156.6 165.2 150.4 153.6 163.1 170.2 116.6 125.4 143.2 152.8 159.7 165.3 149.3 155.6 160.4 167.2 116.5 129.0 140.0 150.5 160.9 167.4 149.2 157.3 167.0 171.5 SIC 33 - PRIMARY METAL INDUSTRIES (Seasonally Adjusted, 1957-59=100) 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. 79.0 92.7 107.6 139.3 154.3 156.6 166.6 160.6 168.0 78.2 94.0 113.3 141.7 154.5 157.7 157.8 162.2 170.7 84.7 78.1 93.5 121.4 147.6 153.8 159.1 157.2 164.7 172.8 85.0 76.8 92.8 123.1 144.6 155.2 159.8 153.6 164.8 168.9 84.6 80.6 92.5 126.0 147.0 153.5 162.6 156.4 165.0 173.4 83.4 83.7 94.6 127.6 148.9 153.8 163.9 157.2 158.1 174.9 83.4 88.4 94.1 128.5 149.4 156.8 165.0 159.2 151.1 176.2 81.8 91.1 95.3 129.6 152.0 157.2 168.2 157.9 143.6 176.6 80.7 92.3 97.5 130.4 155.4 153.4 169.1 157.8 152.0 178.2 80.7 94.1 99.7 131.1 155.9 153.5 170.9 156.4 156.7 183.5 79.9 95.2 101.0 133.2 156.4 152.0 172.7 158.7 160.9 188.9 79.2 95.6 100.4 133.9 155.1 154.1 169.8 159.7 164.9 196.7 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis SIC 34 - FABRICATED METAL PRODUCTS (Seasonally Adjusted, 1957-59=100) 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Jan. Feb. Mar. Apr. May 113.2 116.4 129.7 150.8 163.6 186.3 206.1 208.2 234.3 113.5 117.5 131.7 150.2 163.1 190.1 208.0 209.6 234.1 112.0 111.8 118.2 134.9 151.5 161.5 193.7 210.6 218.4 234.1 109.1 109.6 123.4 138.1 151.0 161.5 195.7 207.2 216.6 233.4 108.3 108.2 122.4 138.8 153.0 161.4 197.9 205.0 217.0 233.0 June Jul^ Aug. Sept. Oct. Nov. Dec. 108.7 107.7 120.9 142.6 155.5 169.8 200.6 202.7 216.7 232.9 111.6 108.6 120.5 144.4 157.4 170.1 201.7 202.9 218.4 232.9 111.6 110.1 118.9 146.8 156.5 173.0 202.4 204.7 220.4 236.0 112.8 113.0 127.7 147.8 155.8 169.7 203.0 209.0 221.8 239.9 110.4 114.9 128.1 146.9 158.4 173.8 203.8 210.0 225.0 243.6 109.2 115.7 131.1 148.8 160.7 177.1 203.3 211.0 228.4 244.4 109.7 116.7 125.0 149.4 162.4 182.6 203.3 207.7 233.9 246.8 SIC 35 - MACHINERY, EXCEPT ELECTRICAL (Seasonally Adjusted, 1957-59=100) 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. 133.7 120.7 133.1 172.1 190.6 211.1 232.7 272.3 286.6 339.7 134.9 120.6 136.5 175.9 187.8 217.7 241.3 272.2 295.9 344.0 136.4 115.0 137.7 177.3 192.1 220.9 247.2 254.9 296.6 339.4 135.8 122.6 144.8 178.0 190.0 224.6 251.3 271.3 300.5 343.6 133.1 125.0 146.2 182.4 190.1 227.6 248.7 273.2 312.9 347.1 133.6 127.7 149.1 176.5 198.2 222.6 256.4 273.8 313.1 356.2 138.1 126.6 151.2 180.1 207.1 240.3 252.5 279.4 322.0 371.5 125.6 130.8 155.5 179.4 200.9 236.0 263.5 276.9 323.4 392.8 129.5 129.9 153.3 186.3 204.7 236.7 261.5 280.4 325.3 384.0 128.3 132.1 156.7 186.1 206.1 241.2 260.1 283.2 332.6 375.6 130.2 135.7 157.0 190.2 203.9 246.9 266.5 281.6 336.8 371.1 125.7 134.2 155.3 189.0 210.7 245.0 267.8 282.6 338.2 361.0 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis SIC 36 - ELECTRICAL MACHINERY (Seasonally Adjusted, 1957-59=100) 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Jan. Feb. Mar. Apr. May 134.9 128.0 187.5 185.2 225.0 259.7 333.5 398.4 429.4 474.8 137.1 131.5 197.7 185.5 225.8 262.3 345.7 396.8 436.5 496.2 139.7 132.2 192.6 190.0 222.4 267.8 358.6 393.9 442.1 497.7 138.0 132.9 187.5 207.0 228.1 268.9 373.4 389.2 446.5 503.1 130.7 136.8 192.0 200.3 230.6 266.5 389.8 385.7 452.2 526.5 June July Aug- Sept. Oct. Nov. Dec. 125.7 138.3 200.3 206.8 236.3 265.2 401.7 383.5 460.3 536.2 123.9 146.4 187.8 208.7 240.5 278.3 394.8 390.1 462.9 558.6 114.5 148.6 175.2 217.9 239.7 296.1 390.1 390.3 493.0 585.1 119.3 150.0 185.3 229.3 241.9 300.7 388.1 393.6 488.1 588.5 117.3 • 158.1 204.4 227.1 245.4 309.6 389.9 401.5 482.2 582.5 111.3 155.4 190.3 231.1 245.8 316.0 391.2 409.0 470.9 571.1 113.0 160.2 184.9 231.8 251.3 325.0 395.4 419.6 476.3 558.4 SIC 37 - TRANSPORTATION EQUIPMENT (Seasonally Adjusted, 1957-59=100) Jan. 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 85.0 103.9 142.8 178.4 195.8 238.9 241.1 277.2 314.5 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. 84.5 108.1 144.6 179.5 203.6 239.1 264.4 281.9 326.4 96.7 83.7 111.2 147.4 186.1 205.5 246.4 250.6 281.5 335.8 98.0 85.8 112.7 149.2 184.3 214.7 245.5 256.1 263.8 329.9 96.1 85.2 114.3 155.5 186.6 216.7 246.4 263.2 288.9 332.4 100.7 84.2 121.5 155.2 192.1 216.7 242.6 268.7 301.1 333.0 100.7 86.6 122.6 157.4 195.3 221.2 250.6 264.4 304.4 338.5 103.2 89.6 127.8 159.9 186.8 227.7 248.7 270.4 307.3 365.6 97.2 90.1 129.3 163.6 192.3 216.7 257.5 273.0 301.3 353.2 104.8 89.8 132.4 168.0 190.7 232.0 267.7 270.5 318.7 366.7 100.5 97.7 133.2 170.1 193.7 241.4 251.6 274.4 325.1 369.7 95.1 100.9 131.7 169.9 206.1 240.2 257.9 273.9 322.2 353.4 TOTAL NONDURABLE GOODS INDUSTRIES (Seasonally Adjusted, 1957-59=100) 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Jan. Feb. Mar. Apr. May 114.4 120.3 127.9 139.5 152.3 166.3 174.6 178.3 190.2 114.9 122.7 128.7 140.4 153.1 168.9 174.3 180.6 191.9 114.8 123.4 130.1 140.8 154.6 168.5 174.8 182.1 192.9 115.2 123.9 131.4 141.7 156.2 169.4 175.2 182.5 194.4 115.9 124.3 132.1 141.4 157.1 169.0 175.0 184.6 195.9 June July Aug. Sept. Oct. Nov. Dec. 113.6 116.6 125.5 133.0 143.7 158.4 169.6 177.2 186.8 198.7 114.4 117.5 126.4 134.9 145.4 158.4 170.9 176.6 186.9 201.0 114.0 118.3 126.5 133.9 146.6 160.0 171.6 177.0 188.3 200.8 113.7 119.1 127.2 134.7 146.9 160.7 172.5 177.5 188.8 202.8 113.3 119.7 127.6 136.4 147.9 162.3 173.0 177.6 189.6 210.7 113.0 120.4 128.3 136.9 149.6 163.5 173.5 178.0 190.7 212.0 112.9 121.5 128.2 138.6 150.9 165.1 173.8 178.8 191.8 213.0 TOTAL DURABLE GOODS INDUSTRIES (Seasonally Adjusted, 1957-59=100) Jan. 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 101.5 115.6 137.1 161.5 178.2 201.5 215.7 225.8 252.4 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Feb. 101.0 121.4 139.1 160.4 180.5 203.8 218.3 230.0 259.3 Mar. Apr. 99.7 122.0 143.0 165.9 181.6 207.9 214.1 232.1 260.0 100.2 122.7 146.7 165.3 184.9 210.4 214.6 229.5 259.1 May June July Aug. Sept. Oct. Nov. Dec. 101.3 124.1 148.9 166.9 185.1 212.1 215.5 237.5 263.0 105.6 102.4 127.2 150.3 168.8 185.4 213.9 216.6 240.5 266.0 106.3 105.2 126.5 152.1 171.5 190.5 214.8 217.1 241.5 271.0 104.4 108.1 126.8 154.2 172.0 193.7 215.6 218.4 244.0 281.5 103.4 109.2 129.9 157.3 170.9 190.5 217.7 220.1 244.3 279.5 104.8 110.4 133.4 158.4 173.7 195.8 220.0 220.6 249.1 282.4 102.9 113.3 129.8 160.1 175.0 199.4 217.5 223.0 250.8 282.1 101.2 114.9 130.3 159.9 178.5 201.5 218.6 224.3 253.3 278.7 TOTAL MANUFACTURING (Seasonally Adjusted, 1957-59=100) 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. 108.3 118.2 132.1 149.5 164.0 182.4 193.1 200.0 218.5 108.4 122.1 133.6 150.8 165.7 183.8 194.3 203.2 222.3 107.9 122.8 136.0 152.1 166.7 185.8 192.8 204.9 223.4 108.2 123.4 138.4 152.4 169.0 187.9 193.1 203.9 223.8 109.3 124.2 139.7 152.9 169.7 188.7 193.4 208.5 226.4 109.9 110.3 126.2 140.9 155.6 170.4 189.7 195.0 211.3 229.3 110.6 112.0 126.5 142.0 157.4 173.0 190.7 194.9 211.5 232.8 109.6 113.6 126.6 143.2 157.3 175.3 191.6 196.0 213.6 237.6 108.8 114.5 128.5 145.1 158.5 174.1 193.0 197.0 214.1 237.9 109.4 115.3 130.3 146.2 159.2 177.5 194.0 197.2 216.6 239.6 108.5 117.0 130.1 147.6 161.0 179.8 193.5 198.5 217.8 243.9 107.4 118.3 129.0 148.2 163.4 181.6 194.3 199.4 219.7 242.7 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis i NJ I PRODUCTION INDEX SIXTH FEDERAL RESERVE DISTRICT STATES SIC 20 - FOOD AND KINDRED PRODUCTS (Seasonally Unadjusted, 1957-59=100) APPENDIX C Jan. 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 111.7 113.3 123.2 129.2 137.7 141.4 143.3 144.6 149.7 Feb. 110.5 113.6 121.6 128.1 136.5 140.2 141.5 143.2 148.5 Mar. 110.1 113.1 120.0 125.1 134.7 139.2 141.2 141.0 146.9 Apr. 108.8 112.2 119.3 124.9 134.9 136.9 141.8 140.7 146.9 May June July Aug. Sept. Oct. Nov. Dec. 111.3 114.8 119.2 125.6 135.0 137.6 143.2 143.4 148.9 109.3 113.8 118.2 120.3 128.1 136.0 138.6 148.3 147.8 153.5 112.0 113.7 120.7 120.4 130.9 136.6 140.7 150.2 150.1 158.6 112.0 114.0 120.3 121.8 133.6 137.7 141.7 151.1 152.7 160.1 113'7 115.4 122.8 126.5 136.0 138.7 143.8 152.8 155.5 162.3 114.7 116.8 125.8 129.6 137.1 141.0 144.6 152.3 157.0 164.0 114.6 116.5 126.3 130.9 140.1 142.4 145.8 151.6 157.4 165.5 113.2 114.7 123.2 130.9 139.8 140.9 144.1 148.9 155.8 163.8 -o w i SIC 21 - TOBACCO MANUFACTURES (Seasonally Unadjusted, 1957-59=100) Jan. 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 105.5 100.2 102.3 98.3 98.3 95.3 96.8 84.2 83.8 Feb. 91.7 90.0 87.0 86.5 90.5 84.4 85.1 83.4 83.1 74.5 Mar. 92.7 82.7 80.9 78.6 86.7 78.0 82.8 79.4 76. 7 71.7 Apr. 90.7 79.9 77.4 76.5 87.8 75.4 80.6 78.9 74.9 70.1 May 89.1 79.4 72.3 74.9 84.4 75.1 78.8 79.6 74.0 69.3 June 86.5 80.4 71.0 73.2 82.3 74.1 79.0 75.6 74.1 69.1 July 87.8 83.6 73.2 76.9 80.6 75.9 79.2 76.2 74.8 69.6 Aug. 93.4 89.0 77.9 75.5 80.8 77.8 81.0 78.3 74.4 71.0 Sept. Oct. Nov. Dec. 101.3 94.2 82.7 80.8 84.8 81.8 83.3 85.6 77.4 73.5 105.1 94.2 84.6 82.2 85.6 82.5 85.2 87.6 79.4 75.7 113.6 103.3 98.7 93.7 98.4 93.1 96.5 86.0 88.1 86.3 111.0 102.2 103.4 97.5 99.6 93.9 98.0 86.4 87.0 94.5 SIC 22 - TEXTILE MILL PRODUCTS (Seasonally Unadjusted, 1957-59=100) Jan. 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 113.1 127.0 125.2 136.2 158.8 181.9 190.3 199.1 215.9 Feb. Mar. 113.3 130.2 124.7 139.2 161.9 182.6 188.5 203.3 216.5 113.6 130.3 123.8 140.8 162.5 181.7 185.0 202.9 216.5 Apr. 113.9 129.4 124.4 142.8 164.2 181.9 183.0 200.8 216.6 May June July Aug. Sept. Oct. Nov. Dec. 115.6 129.5 124.7 140.6 165.9 183.2 184.3 202.9 219.2 115.9 116.6 130.6 126.8 150.2 170.5 184.6 187.6 208.5 224.7 114.0 118.2 128.5 125.8 150.1 169.0 185.1 184.2 206.2 223.8 114.0 121.8 131.1 128.5 151.3 174.2 189.4 188.4 212.1 229.6 113.1 124.2 130.5 130.5 151.6 176.2 192.7 192.7 215.1 233.9 112.4 126.1 130.3 133.2 156.7 179.1 193.3 195.9 216.8 232.8 111.9 126.3 129.7 134.0 157.7 181.2 193.5 198.6 219.3 233.7 110.3 125.9 127.2 134.3 157.8 182.3 192.9 200.6 219.5 232.8 i -o -P' SIC 23 - APPAREL AND OTHER FINISHED PRODUCTS (Seasonally Unadjusted, 1957-59=100) 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. 118.1 127.8 152.7 182.3 196.9 211.5 218.8 219.2 243.4 119.4 132.9 152.2 177.6 187.4 203.0 209.9 218.7 235.9 111.0 129.1 152.1 169.8 180.5 193.5 201.2 213.4 226.7 109.6 126.1 153.5 165.3 178.0 192.6 200.8 211.2 223.6 110.4 128.1 162.0 165.8 181.3 189.7 205.4 217.5 227.2 110.2 114.8 133.7 171.7 172.4 188.1 197.0 216.1 227.8 237.9 113.2 119.8 138.3 177.5 179.5 193.8 202.9 219.5 233.0 246.3 119.5 129.1 147.3 189.6 191.0 209.3 217.1 226.9 245.5 256.4 123.4 134.8 154.1 195.0 196.1 217.7 225.1 233.3 253.6 270.1 124.0 138.7 158.5 197.4 202.2 224.3 231.2 236.7 259.3 275.3 124.4 141.8 159.9 197.6 204.2 224.2 230.1 236.3 259.2 277.0 119.5 139.7 155.8 192.5 199.5 219.3 226.4 230.9 252.8 268.6 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis SIC 24 - LUMBER AND WOOD PRODUCTS (Seasonally Unadjusted, 1957-59=100) 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec 93.9 96.1 112.6 124.4 127.6 136.2 143.1 132.6 158.6 93.4 103.0 115.0 126.7 124.8 134.7 137.8 139.7 158.4 92.5 103.4 117.0 127.2 127.5 136.9 138.6 143.3 155.3 93.9 104.7 120.6 127.8 129.8 139.4 137.3 145.2 162.9 96.2 107.0 123.3 128.7 130.3 141.4 135.3 149.6 163.8 102.2 98.8 105.8 126.8 129.3 129.1 141.5 134.2 152.9 166.9 101.0 98.4 105.6 126.2 128.3 129.9 141.5 130.2 156.1 165.9 99.5 101.0 105.6 128.3 127.8 131.7 143.7 134.2 157.3 168.3 99.0 102.0 107.5 128.1 125.6 130.8 144.7 135.5 157.4 168.5 97.1 102.1 108.3 129.4 126.6 134.2 145.3 136.3 157.8 169.0 96.6 101.8 108.9 129.5 129.2 135.4 144.5 136.2 158.3 167.8 93 99 107 128 127 137 145 137 159 168 i -P' SIC 25 - FURNITURE AND FIXTURES (Seasonally Unadjusted, 1957-59=100) 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Jan. Feb. Mar. APr- May June July Aug. Sept. Oct. Nov. Dec 101.8 106.3 127.0 146.5 162.1 179.7 185.3 180.3 198.6 100.4 113.7 129.3 148.5 164.8 181.5 185.2 185.1 200.5 98.7 115.2 130.5 147.2 166.4 181.0 183.5 186.7 199.9 97.5 115.0 130.7 146.2 166.5 179.7 180.1 183.7 199.6 95.9 116.4 131.6 145.8 167.6 177.9 180.0 187.5 194.8 101.9 96.5 118.8 133.4 145.0 168.0 179.4 179.7 190.6 195.7 101.9 98.1 118.3 132.9 142.3 167.2 176.7 178.4 187.7 187.5 104.3 101.7 121.3 137.3 147.1 171.7 181.8 177.9 192.5 194.0 105.3 105.6 125.2 140.1 150.6 173.6 183.7 178.4 193.7 193.8 105.8 107.1 125.8 143.0 154.7 176.2 185.7 177.9 195.4 193.0 104.0 109.2 126.5 144.3 156.6 178.9 187.2 180.6 196.6 192.2 103 111 126 145 160 181 187 185 200 189 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis SIC 26 - PAPER AND ALLIED PRODUCTS (Seasonally Unadjusted, 1957-59=100) 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. 120.3 124.0 128.3 129.4 143.4 158.5 171.4 174.3 181.6 117.9 123.4 128.0 130.9 143.4 159.2 171.1 174.2 183.1 120.1 125.0 128.6 133.7 146.0 163.6 173.5 175.5 185.6 120.3 126.4 125.3 134.8 145.9 166.4 170.4 175.4 188.3 121.4 127.2 125.0 136.8 147.5 167.7 170.3 177.0 193.0 120.3 123.6 130.3 124.9 139.7 150.9 172.3 173.5 178.4 197.5 119.7 124.1 129.9 124.5 140.8 151.2 173.7 173.3 178.9 198.7 121.9 126.6 132.5 125.6 141.6 152.0 173.7 173.6 180.0 199.2 119.7 125.1 131.2 121.2 141.2 152.4 173.1 173.6 178.8 200.1 120.7 126.3 132.3 126.2 142.0 153.7 174.2 173.9 178.8 201.0 119.1 126.2 132.0 126.2 141.8 154.4 174.2 173.8 179.0 200.0 117.9 125.7 132.0 125.9 142.1 155.6 171.7 173.7 179.7 201.5 i -o SIC 27 - PRINTING, PUBLISHING, AND ALLIED INDUSTRIES (Seasonally Unadjusted, 1957-59=100) 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Jan. Feb. Mar. Apr. May June July Aug. Sept- Oct. Nov. Dec. 115.5 114.6 113.4 127.2 133.0 151.7 165.2 165.2 167.5 109.6 111.1 108.4 122.2 130.5 147.1 159.7 159.8 162.3 106.6 107.4 104.6 118.6 127.6 145.1 155.7 156.3 157.3 101.3 105.5 105.6 117.0 127.8 143.0 154.9 155.2 154.9 101.0 107.0 109.7 117.3 130.6 144.7 156.9 156.3 154.7 106.0 102.1 107.9 112.0 119.6 133.8 148.1 157.7 160.0 158.5 111.3 105.8 113.0 116.7 124.9 138.6 154.2 162.5 163.7 164.4 116.3 111.0 118.8 122.5 130.5 144.5 160.6 166.3 170.4 171.0 120.7 115.8 122.2 129.1 135.3 151.3 166.1 169.8 175.2 176.4 123.9 118.6 122.7 131.2 137.9 155.5 170.6 172.0 177.1 179.1 123.9 118.8 120.8 131.5 138.3 156.1 172.0 171.3 177.2 180.7 121.0 120.2 118.6 130.7 137.9 155.4 171.0 170.7 175.4 179.1 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis SIC 28 - CHEMICALS AND ALLIED PRODUCTS (Seasonally Unadjusted, 1957-59=100) 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec 123.9 132.9 147.3 170.9 170.7 196.2 214.8 231.2 250.0 122.6 127.4 144.2 168.3 172.0 194.2 214.7 230.7 248.2 111.4 122.8 124.0 147.4 167.6 176.0 193.4 216.8 231.9 248.1 113.3 123.3 125.8 149.3 169.6 180.5 197.0 217.2 235.0 252.1 114.6 128.3 130.8 154.8 172.7 183.7 203.3 221.0 238.1 257.0 112.7 129.5 131.0 153.0 173.0 186.0 205.4 224.9 240.1 257.1 110.2 126.4 132.7 154.2 170.4 187.0 207.0 228.7 240.5 258.6 109.2 122.2 132.3 152.8 168.3 188.1 208.1 229.8 240.8 257.2 110,3 120.4 135.8 153.4 168.0 187.8 208.6 229.5 245.7 261.5 115.4 123.7 140.7 156.2 168.7 190.0 208.4 230.3 249.6 263.1 118.3 128.4 144.8 162.9 168.5 190.5 208.6 231.3 250.9 263.4 122 134 147 169 169 195 210 233 252 262. i SIC 29 - PETROLEUM REFINING AND RELATED INDUSTRIES (Seasonally Unadjusted, 1957-59=100) 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 1 Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec 104.0 102.0 103.4 124.1 124.6 134.7 137.5 150.2 146.2 121.2 106.7 104.8 116.0 121.4 135.3 131.1 148.0 152.9 108.5 139.4 112.2 108.2 108.7 119.0 136.2 124.6 146.5 167.8 113.0 144.6 113.5 108.5 111.1 117.8 137.3 129.3 144.6 167.1 113.8 135.3 116.5 112.3 115.4 120.5 140.0 138.2 147.9 174.5 104.6 120.4 118.8 115.6 121.3 123.5 141.5 153.6 152.3 175.4 98.9 103.4 119.2 118.6 124.5 128.5 143.4 158.7 152.2 182.4 92.3 99.3 120.9 119.3 128.2 133.7 143.7 150.9 148.7 176.2 94.8 99.7 114.4 122.1 129.6 132.8 147.6 139.9 150.4 170.9 90.5 99.7 108.8 128.3 128.4 131.2 147.9 135.9 152.4 166.9 89.1 98.0 100.6 132.4 127.0 128.4 148.5 148.4 150.1 165.9 87 96 100 133 125 130 145 156 140 163 SIC 30 - RUBBER AND MISCELLANEOUS PLASTIC PRODUCTS (Seasonally Unadjusted, 1957-59=100) 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. 113.4 132.8 140.3 160.5 181.6 232.5 253.3 277.9 323.7 114.6 131.7 146.2 156.1 186.6 232.9 250.6 276.5 329.1 116.5 131.7 151.8 157.7 192.7 233.5 246.3 281.5 326.9 118.3 130.2 154.7 158.6 198.6 234.4 243.7 279.5 331.4 122.2 130.3 154.3 161.0 207.5 235.6 224.9 284.2 335.1 116.5 126.1 131.4 156.5 161.2 217.9 234.6 231.2 293.0 342.1 116.0 126.1 129.8 162.1 160.7 214.6 235.4 225.6 288.1 344.9 115.5 127.6 131.2 154.4 171.8 224.7 240.3 255.0 298.3 351.4 114.3 129.2 133.5 156.6 175.6 223.3 243.5 260.1 305.1 363.2 115.2 131.4 136.8 161.8 175.8 226.9 246.3 264.2 309.1 368.5 112.6 131.4 139.1 158.5 175.4 227.7 247.4 268.9 317.6 375.5 110/ 132/ 141/ 160/ 175.: 231/ 245/ 267/ 319/ 381/ I oo I SIC 31 - LEATHER AND LEATHER PRODUCTS (Seasonally Unadjusted, 1957-59=100) 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Jan. Feb. Mar. Apr. May June July Aug. Sept. 99.5 106.8 110.3 129.9 140.8 147.9 156.2 160.6 167.6 99.6 105.9 110.2 129.4 143.1 152.8 153.8 158.9 164.7 99.4 98.1 102.8 109.3 126.6 138.4 151.4 152.9 156.2 160.1 96.6 95.5 100.1 109.6 123.1 134.0 149.8 149.7 157.0 158.5 95.5 96.0 101.2 114.0 126.2 131.3 149.0 149.5 157.4 157.0 98.0 97.2 102.8 121.6 132.1 131.1 153.6 151.3 162.2 156.9 102.8 98.5 105.9 126.7 138.4 135.9 159.9 154.8 166.6 154.5 105.0 99.5 106.5 131.0 140.8 140.1 163.7 156.9 168.2 151.9 103.8 101.4 108.3 129.2 140.9 145.3 163.0 157.6 166.3 149.0 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Oct. 100.5 102.6 107.6 128.0 138.9 146.1 159.8 158.0 165.2 149.2 Nov. 98.9 103.6 107.6 125.0 136.9 144.8 158.3 160.1 166.2 153.4 Dec. 99 105 107 127 138 145 156 162 168 159 SIC 32 - STONE, CLAY, GLASS, AND CONCRETE PRODUCTS (Seasonally Unadjusted, 1957-59=100) 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Jan. Feb. Mar. Apr. May June Jul^ Aug. Sept. Oct. Nov. Dec. 113.6 113.6 111.6 135.6 138.4 156.0 156.0 142.4 148.1 159.0 111.5 113.0 126.9 133.8 145.9 156.0 151.7 140.5 147.3 164.1 107.5 112.6 133.1 140.8 150.2 159.6 155.8 147.0 150.0 163.7 120.7 114.7 136.3 146.2 154.1 165.6 160.1 149.7 155.6 163.1 118.6 118.8 142.4 153.3 158.8 171.1 157.3 151.5 161.2 166.1 121.3 121.1 146.9 156.9 161.5 173.0 158.5 156.1 168.7 172.4 120.1 122.7 147.1 157.4 160.2 175.0 157.7 155.9 167.9 175.4 119.4 127.3 147.7 157.0 160.4 173.6 156.9 157.9 166.9 172.9 115.3 126.6 146.9 155.8 155.0 167.6 154.2 155.4 166.1 170.9 119.2 120.1 145.4 154.9 157.1 165.3 150.3 153.4 162.9 170.0 115.9 124.6 142.4 152.4 159.6 165.6 149.9 156.3 161.1 168.0 111.6 123.5 134.3 145.1 156.0 163.4 146.8 155.5 165.3 170.0 I SIC 33 - PRIMARY METAL INDUSTRIES (Seasonally Unadjusted, 1957-59=100) 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. 77.7 91.3 106.1 137.5 152.8 155.6 165.8 160.0 167.3 78.2 94.0 113.3 141.4 154.0 156.9 156.6 160.7 169.0 85.9 79.2 94.8 122.8 148.7 154.3 159.0 156.5 163.7 171.6 88.1 79.6 96.2 127.4 149.2 159.5 163.5 156.6 167.6 171.6 87.3 83.2 95.4 129.9 151.2 157.6 166.6 160.0 168.7 177.2 86.3 86.6 97.8 131.7 153.2 157.7 167.5 160.3 161.1 178.0 84.6 89.6 95.4 130.1 151.2 158.3 166.5 160.4 152.1 177.4 81.8 91.1 95.3 129.6 152.1 157.3 168.5 158.2 143.9 177.0 79.8 91.3 96.4 129.1 153.9 152.0 167.5 156.2 150.4 176.2 78.2 91.2 96.7 127.5 151.8 149.7 166.9 153.0 153.2 179.5 76.3 90.9 96.6 128.0 151.1 148.0 169.3 156.3 158.8 186.4 76.8 92.8 97.6 130.7 152.1 152.0 168.6 159.2 164.6 196.3 SIC 34 - FABRICATED METAL PRODUCTS (Seasonally Unadjusted, 1957-59=100) 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. 110.2 113.6 127.1 148.3 161.5 184.5 204.1 206.2 232.2 109.4 113.4 127.4 145.7 159.0 186.3 204.3 206.2 230.4 107.3 107.1 113.3 129.4 145.5 155.6 187.3 204.1 212.0 227.3 106.5 106.9 120.3 134.4 146.8 157.2 191.0 202.7 212.3 229.0 108.0 107.9 122.0 138.2 152.0 160.2 196.3 203.4 215.3 231.1 111.5 110.5 124.1 146.4 159.5 173.9 204.8 206.3 220.2 236.4 113.6 110.6 123.0 147.8 161.6 174.9 207.5 208.4 224.0 238.7 114.6 113.1 122.2 151.0 161.0 178.0 208.2 210.4 226.4 242.4 113,9 114.1 128.8 148.9 156.9 170.8 204.6 210.8 223.8 242.1 112.7 117.3 130.5 149.2 160.1 175.0 204.9 211.2 226.2 244.8 110.8 117.4 132.8 150.4 161.8 177.8 203.8 211.3 228.6 244.6 110.8 117.9 126.2 150.6 163.1 182.7 203.1 207.1 232.9 245.6 i tn O I SIC 35 - MACHINERY, EXCEPT ELECTRICAL (Seasonally Unadjusted, 1957-59=100) 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Jan. Feb. Mar. Apr. May June July Au8- Sept. Oct. Nov. Dec. 131.0 118.2 130.4 168.4 186.1 205.8 226.6 264.3 277.9 329.2 136.1 121.7 137.6 176.9 188.2 217.7 241.2 271.8 295.6 343.7 134.2 113.2 135.7 175.0 189.5 217.9 243.4 250.2 290.7 332.3 137.8 124.4 146.8 180.1 191.5 225.5 251.4 270.7 299.6 342.6 136.4 128.1 149.5 185.6 192.5 229.4 250.1 274.4 314.3 348.8 137.5 131.4 153.5 181.8 204.1 229.5 264.4 282.4 322.9 367.2 131.9 120.9 144.7 172.9 199.8 233.0 246.0 272.9 314.7 363.3 129.8 135.1 160.4 184.8 206.4 242.0 270.0 284.0 331.7 403.0 131.8 132.3 156.3 190.5 210.0 243.3 269.0 288.2 334.3 394.4 127.5 131.2 156.0 185.9 206.5 242.5 262.5 286.3 336.1 379.7 127.1 132.4 153.3 186.2 200.4 243.4 264.2 279.8 335.1 369.2 123.6 131.9 152.9 186.5 207.9 241.4 263.6 277.6 331.4 353.8 SIC 36 - ELECTRICAL MACHINERY (Seasonally Unadjusted, 1957-59= 100) 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Jan. Feb. Mar. Apr. May June JulX Au8- Sept. Oct. Nov. Dec. 130.7 124.0 181.8 179.7 218.6 253.3 326.8 391.5 423.0 468.2 134.5 129.0 193.9 181.6 220.7 256.8 339.5 390.7 430.6 489.8 137.5 130.0 189.3 186.6 218.3 263.3 353.8 389.9 438.7 494.7 134.3 129.3 182.9 202.7 224.7 266.7 372.4 389.1 447.1 504.1 132.0 138.1 193.6 201.7 231.8 267.8 391.8 388.2 455.8 531.2 126.2 138.8 201.3 208.3 238.5 268.1 406.0 387.3 464.6 541.0 123.5 145.9 187.3 208.1 239.9 278.0 394.8 390.4 463.1 558.6 116.1 150.7 177.7 221.1 243.0 299.6 394.4 394.1 497.3 589.8 121.1 152.3 188.3 233.4 246.4 305.9 394.0 398.5 493.5 594.4 120.5 162.3 209.8 232.6 250.2 313.9 393.5 403.6 483.5 584.3 115.0 160.6 196.1 237.2 250.3 319.2 392.9 409.4 470.8 570.5 112.2 159.0 183.5 230.1 249.4 322.2 392.2 415.9 472.3 553.9 l_n H* I SIC 37 - TRANSPORTATION EQUIPMENT (Seasonally Unadjusted, 1957-59=100) 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. 85.5 104.3 142.4 176.3 191.9 232.3 232.8 266.9 302.2 87.6 112.0 149.4 184.5 208.2 243.5 268.3 285.5 330.3 95.1 82.2 109.2 144.4 181.1 198.5 235.7 237.9 266.1 317.0 98.8 86.5 113.6 150.2 185.0 214.8 245.1 255.0 262.3 327.6 97.2 86.2 115.6 157.1 188.6 218.5 248.1 264.1 289.7 333.4 103.5 86.6 124.8 159.4 196.9 222.2 248.7 275.6 308.9 341.7 101.7 87.5 124.0 159.7 198.7 225.8 256.4 271.0 312.1 347.0 104.2 90.5 129.1 161.4 188.7 230.3 252.6 275.4 313.4 373.3 96.7 89.7 129.1 164.6 195.2 221.7 264.6 280.9 310.3 353.5 102.7 88.0 129.8 165.1 187.9 229.4 265.8 269.5 317.9 366.0 97.7 95.0 129.8 166.5 190.6 239.0 251.1 274.9 326.0 370.8 91.4 97.0 127.0 164.7 200.7 234.8 253.0 268.9 316.0 346.7 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis TOTAL NONDURABLE GOODS INDUSTRIES (Seasonally Unadjusted, 1957-59=100) Jan. 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 116.5 122.4 130.5 141.8 154.8 169.6 184.5 178.9 191.2 Feb. 115.3 123.2 129.4 140.6 153.6 168.0 172.0 178.5 189.6 Mar. 114.2 122.3 128.7 139.1 152.5 166.7 169.8 177.1 187.6 APr- 113.1 121.4 128.5 138.5 152.8 166.3 168.8 176.1 187.6 May June July Au£- Sept. Oct. Nov. Dec. 114.9 123.3 130.3 139.2 154.7 166.7 169.4 178.7 190.1 113.8 116.1 126.1 132.9 143.6 158.2 169.8 174.4 184.1 195.6 115.4 118.5 125.7 134.4 146.4 159.6 172.6 175.2 185.5 199.1 117.2 121.8 130.6 137.6 150.2 164.2 176.2 178.9 190.5 203.0 117.8 123.7 132.1 140.4 152.4 166.9 179.3 182.0 193.8 207.7 118.7 125.6 134.3 143.2 155.0 169.8 181.1 183.4 195.5 209.7 118.4 126.2 134.4 143.5 156.2 170.9 181.6 183.8 196.7 210.9 116.5 125.7 132.6 143.2 156.0 170.6 179.7 182.4 195.4 209.7 TOTAL DURABLE GOODS INDUSTRIES (Seasonally Unadjusted, 1957-59=100) 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. 102.3 114.2 138.1 160.5 175.3 200.1 211.3 221.1 247.1 103.9 124.5 142.0 163.8 181.0 207.1 126.5 228.0 256.9 99.4 123.7 143.6 165.4 179.6 208.3 209.3 226.7 253.4 104.9 127.0 150.9 168.2 190.1 216.7 214.3 229.4 258.3 107.7 128.2 155.4 171.3 191.0 214.7 216.9 239.0 264.5 112.7 109.2 134.0 159.0 177.2 193.3 224.4 220.7 244.9 270.8 109.7 109.3 129.6 156.3 173.7 193.6 221.7 219.2 243.6 273.5 110.1 113.5 130.7 160.6 175.2 199.3 227.9 221.7 247.8 285.8 108.3 113.8 136.0 163.8 178.2 197.3 230.0 223.2 248.0 281.2 108.9 114.7 136.4 163.3 175.9 200.1 227.7 220.5 249.2 282.4 105.3 116.2 134.4 163.0 176.4 203.0 226.0 222.8 250.6 282.0 103.5 115.7 130.9 160.8 178.5 200.7 224.4 222.5 251.0 276.3 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis TOTAL MANUFACTURING (Seasonally Unadjusted, 1957-59=100) Jan. Feb. Mar. Apr. Maj. June July Aug- Sept. Oct. Nov. Dec 110.5 119.5 134.7 150.8 165.0 184.3 191.6 198.1 247.1 110.6 124.6 135.7 151.7 166.7 186.4 192.4 201.3 256.9 108.3 123.6 136.2 151.6 165.5 186.5 187.8 199.8 253.4 110.2 124.6 139.4 152.9 170.5 190.0 189.6 200.2 258.3 112.4 126.2 142.6 154.5 171.7 189.4 191.1 206.3 264.5 113.9 113.5 130.3 145.7 159.7 175.1 195.6 195.5 211.6 270.8 113.5 115.1 129.1 145.2 159.7 176.0 195.7 195.1 211.9 273.5 114.4 118.6 131.2 148.5 162.5 180.8 200.5 198.2 216.5 285.8 113.9 119.5 134.. 5 151.8 164.9 181.4 203.3 201.2 218.4 281.2 114.8 121.4 135.7 153.0 165.2 184.6 203.1 200.3 220.8 282.4 113.0 122.2 135.1 153.2 166.2 186.5 203.0 201.6 221.8 282.0 111 121 132 151 167 185 201 200 221 276 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis i Ln GO I -54- BIBLIOGRAPHY Books Dunlop, John T., and Diatchenko, Vasilii P., Labor Productivity. McGraw-Hill Book Company, 1964. New York, Hultgren, Thor, Changes in Labor Cost During Cycles in Production and Busi ness (New York, National Bureau of Economic Research, 1960), Chapter 2. ______ , Cost, Prices, and Profits: Their Cycle Relations. Bureau of Economic Research, 1965. New York, National Kendrick, John W., Productivity Trends in the United States. Princeton University Press, 1961. Princeton, Kendrick, John W., and Creamer, Daniel, Measuring Company Productivity. York, National Industrial Conference Board, 1965. Macaulay, Frederick R., The Smoothing of the Time Series. Bureau of Economic Research, 1931. New New York, National Seasonal Adj ustment on Electronic Computers. Organization for Economic Co operation and Development (report and proceedings of an international conference held in November 1960). Articles A symposium on CES Production Functions, Review of Economics and Statistics, Vol. 50, 1958, pp. 443-479. Anderson, L. C., "Value Added by Manufacture, Central Mississippi Valley Metro Areas, 1957-64." Review, Federal Reserve Bank of St. Louis. June 1964 David, Faul A., "The Deflation of Value Added." Statistics, Vol. 44, 1962, pp. 148-155. Review of Economics and Davis, C. Howard, "Improvement of Texas Industrial Production Index." ness Review, Federal Reserve Bank of Dallas, September 1968. Busi Dhrymes, Phoebus J., and Zarembka, Paul, "Elasticities of Substitution for Two-Digit Manufacturing Industries: A Correction." Review of Economics and Statistics, Vol. LII (February 1970). "Electric Power - An Indicator of Industrial Activity." New England Business Review, Federal Reserve Bank of Boston, February 1965. "Electric Power as a Regional Economic Indicator." Reserve Bank of Cleveland, September 1964. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Economic Review, Federal -55- "Electric Power Consumption - An Output Indicator in Milwaukee.” Conditions, Federal Reserve Bank of Chicago, April 1962. ’’Electric Power Consumption in Manufacturing.” Reserve Bank of Philadelphia, April 1961. Business Business Review, Federal Fisher, Franklin M., ’’Embodied Technology and the Existence of Labour and Output Aggregated." Review of Economic Studies, Vol. 35 (1968). ______ , "The Existence of Aggregate Production Function." 37 (1969). Econometrica, Vol. Gallaway, Lowell E., "Regional Capital Estimates by Industry, 1954-57." Southern Economic Journal, Vol. XXIX (July 1962). Kuh, Edwin, Profits, Profits Markups, and Productivity. Joint Economic Committee, 86th Congress, Government Printing Office, 1960. Lovell, C. A. Knox, "Biased Technical Change and Factor Shares in the U. S. Manufacturing." Quarterly Review of Economics and Business, Vol. 9 (Autumn 1969). Nerlove, Marc, "Recent Empirical Studies of the CES and Related Production Functions," in Murray Brown, ed., The Theory and Empirical Analysis of Production (New York, National Bureau of Economic Research, 1967). Pyun, C. S., "The Southeast’s Booming Paper Industry." eral Reserve Bank of Atlanta, September 1969. Monthly Review, Fed Shen, T. Y., "Innovation, Diffusion, and Productivity Changes." Economics and Statistics, Vol. 43 (1961). Review of Solow, Robert M., "Some Recent Developments in the Theory of Production," in Murray Brown, ed., The Theory and Empirical Analysis of Production (New York, National Bureau of Economic Research, 1967). "Toward an Index of Ninth District Industrial Production." Monthly Review, Federal Reserve Bank of Minneapolis, June 1966. Wilson, Thomas A., and Eckstein, Otto, "Short-run Productivity Behavior in U. S. Manufacturing." Review of Economics and Statistics, Vol. 46 (1964). Zarembka, Paul, "On the Empirical Relevance of the CES Production Function." Review of Economics and Statistics, Vol. LII (February 1970). Government Publications Gehman, Clayton, and Metheral, Cornelia, Industrial Production Measurement in the United States: Concepts, Uses, and Compilation Practices. Washington, Board of Governors of the Federal Reserve System, February 1964. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis -56- Industrial Production, 1959 Revision. Federal Reserve System, 1960. Washington, Board of Governors of the U. S. Bureau of Census, Annual Survey of Manufactures. ______ , Census of Manufactures. Various volumes. 1957 and 1963. U. S. Bureau of Labor Statistics, Employment and Earning Statistics for the ILSL, 1909-68. Bulletin No. 1312-6, 1968. ______ , Trend in Output Per Man-hour in the Private Economy, 1909-1958. Bulletin No. 1249, December 1959. Others Business Indexes Proposed for the Fifth District (mimeograph). serve Bank of Richmond, undated. Federal Re Estle, Edwin E., and Fair, Jerilyn, "Electric Power - An Indicator of Indus trial Activity - Technical Supplement" (mimeograph). Federal Reserve Bank of Boston, 1965. Grose, Lawrence, "Derivation of Quarterly and Monthly Correction Factors of the Bassie Method." U. S. Department of Commerce memorandum, June 11, 1942 Long, Richard, Measuring Regional Production, a proposal. Bank of Atlanta, undated. Federal Reserve "Measuring New England’s Manufacturing Production - Technical Supplement" (mimeograph). Federal Reserve Bank of Boston, October 1963. Minutes of the Workshop on Local Production Indexes, (the conference was held at the Federal Reserve Bank of Cleveland in April 1964). Federal Reserve System. Hale, Carl W., Methodology of the Texas Industrial Production Index, 1966 re vision (mimeograph). Federal Reserve Bank of Dallas, July 1966. Shen, T. Y., A Regional Production Index for New England (mimeograph). Federal Reserve Bank of Boston, 1960. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Boston
