Abstract
The paper follows Kalecki’s ‘golden rules’ under which historical materialism and econometrics can be reconciled provided that changes in the superstructure are not of such a magnitude as to invalidate the use of econometrics to estimate the relationships between the economic variables in the sector of productive activity and that productive relations are explicitly included in the model. Econometric estimates of the determinants of non-farm, non-financial capital goods in the USA 1992–2010 are presented. Statistically significant relationships are found between investment orders and cyclical variations in output, the interest rate spread, net cash flows, the net increase in financial liabilities, the net increase in financial assets, and the value of non-defense manufacturing shipments.
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- 1.
We thank Jerry Courvisanos for this clarification.
- 2.
As described below in Appendix 2, our data on cash flows, the net increase in liabilities and the acquisition of financial assets are derived from U.S. flow of Funds Accounts. In these accounts, Capital Expenditures = Total Internal Funds (plus the Inventory Valuation Adjustment) plus the Net Increase in Liabilities minus the Net Acquisition of Financial Assets plus the Statistical Discrepancy. Again, we do not expect problems of simultaneity as investment orders lead investment expenditures.
- 3.
Sawyer (1986, pp. 51–52) explains the analogous relationship between sales and profits in the investment equation.
- 4.
These two periods basically cover the last two business cycles as defined by NBER Business Cycle Dating Committee.
- 5.
The Flow of Funds Accounts provide a much higher level of aggregation than does the Census Bureau‘s NAICS measure of New Orders of Non Defense Capital Goods. We suspect that this high level of aggregation accounts for the statistically insignificant results.
- 6.
The measure of potential real GDP used is generated by the Congressional Budget Office and provided by FRED.
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Appendices
Appendix 1: Summary Statistics
Appendix 2: Empirical Definitions
Our data are derived from four main sources: (1) The U.S. Census of Manufacturers (Manufacturer’s Shipments, Inventories, and Orders: Historic Timeseries Accounts (NAICS Based); (2) The Federal Reserve’s Flow of Funds Accounts; (3) The National Income and Product Accounts of the U.S; and (4) The Federal Reserve Economic Data (FRED database) provided by the St. Louis Federal Reserve Bank.
Investment orders (D): For the dependent variable, investment orders of non-defense new capital goods, as published by the Census Bureau, was used. The Census Bureau provides monthly data. The monthly data were converted into quarterly data by summing up the three months of data and by dividing that sum by 3. We used the NAICS time series. This series is available from 1992, second quarter to date.
Profits (P): For the profit variable, total internal funds plus the inventory valuation adjustment of non-farm non-financial corporations (which excluded dividends) is used. In addition to the profits variable, we consider the affects of the net increase in liabilities (nil) and the net acquisition of financial assets (naf) on new orders. The net acquisition of financial assets minus the net increase in financial liabilities equals net lending, if positive, or net borrowing, if negative. These series of data are provided by the Federal Reserve in the Flow of Funds Accounts of the United States.
Gearing (or leverage) ratio (g): Two measures of the gearing ratio were considered: (1) Debt to Net Worth; and (2) Debt to Equity. Both series are provided in Table B.102, lines 36 and 37. These series did not generate statistically significant results, and the series is excluded from estimates below.Footnote 5
Capacity utilisation (c): We considered three empirical definitions of the capacity utilization rate: (1) Total Industrial Capacity Utilization provided by FRED; (2) Manufacturing Capacity Utilization, also provided by FRED; and (3) The cyclical variation in output. The cyclical variation in output was computed as the difference between current real GDP and ‘potential’ real GDP as a percent of real ‘potential’ GDP.Footnote 6 Total Industrial Capacity Utilization and the cyclical variation in output variables were highly correlated. The cyclical output variable generated slightly better estimates (see below) and was used as our capacity utilization measure.
The interest rate spread (s). The interest rate spread is calculated as the difference between the yield on the 10 Year (constant) maturity Treasury Bond and the Federal Funds Rate as provided by FRED.
The Sales Accelerator (sa). The sales accelerator is the change in seasonally adjusted manufacturing value of shipments (excluding) defense as provided by the Census of Manufacturing. Shipments, instead of orders, were used, because our dependent variable includes a subset of manufacturing orders.
The wage share (w). The wage share is calculated as non-financial corporation’s compensation to employees divided by the respective value added and this series is provided in Table 1.14 in the National Income and Product Accounts.
Defense Spending(d). The defense spending variable is measured as the ratio of National Defense and Consumption Expenditures and Gross Investment (Table 3.115 of the NIPA) to Nominal GDP.
The nominal levels of new orders, internal funds, the net increase in liabilities, the net acquisition of financial assets, and the value of manufacture shipments were converted into constant dollars using the nonresidential fixed investment price index provided in the National Income and Product Accounts, Table 1.1.4, line 9. These constant dollar levels were divided by real ‘potential’ GDP to reflect cyclical variations in variables and to ensure that the variables have similar units of measurement.
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Charos, E., Kazemi, H.S., Laramie, A.J., Mair, D. (2016). A Kaleckian Model of New Orders of Non-defense Capital Goods in the USA 1992–2010. In: Katsikides, S., Hanappi, H. (eds) Society and Economics in Europe. Springer, Cham. https://doi.org/10.1007/978-3-319-21431-3_13
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