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A nonparametric panel data approach to the cyclical dynamics of price-cost margins in the fourth Kondratieff wave

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Abstract

By using nonparametric and panel data econometrics, this paper re-assesses the effect of both the current level of economic activity and of future expected demand on the dynamics of the price mark-up over marginal cost in US manufacturing industries from 1958 to 1996. Consistently with previous results, the current level of economic activity has a negative impact on the mark-up and expectations of future demand a positive one. Differences between consumer and producer goods and between more and less competitive sectors play a minor role. Differences between durable and non-durable goods, instead, find more empirical support.

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Notes

  1. Given that we leave the production function unspecified we do not need to take logs of the variables, nor to introduce possible nonlinear effects or to assume additively separable adjustment costs as in Galeotti and Schiantarelli (1998).

  2. Our variables are measured as follows. Gross output is the total value of shipments in $1,000,000. Mt is the total cost of materials in $1,000,000. Energy is the cost of electricity and fuels in $1,000,000. The total real capital stock is measured in $1,000,000, while total employment is in thousands and total hours in millions.

  3. For a broader description of the dataset see http://www.nber.org/nberces.

  4. However, there exist several reasons why a negative marginal product might exist in the long-run as well. It might be due to a negatively sloped supply function of a given input (for instance due to economies of bulk purchase). One further reason is that a given input might require a minimum scale of production, under which it might entail costs that outweigh those of other variable production inputs. On this issues see Miller (1970), Ng (1972), Glustoff and Wickham (1991) and Ferguson (1969). Detecting what exactly is the specific case for the roasted coffee industry in the US is beyond the scope of this paper, all the more that it was not significantly different from zero.

  5. The fact that we found evidence of negative short run marginal product implies that (9) cannot be specified in a logarithmic form.

  6. We specifically used Baltagi’s EC2SLS estimator. Using the G2SLS estimator by Balestra and Varadharajan-Krishnakumar would not change our results as well as using the Baltagi and Chang variance component estimator. For an introduction to these estimators see Baltagi (2001).

  7. Experimenting with the second lag of Lt would yield similar results.

  8. Drukker (2003) found that it has good properties in reasonable sample sizes.

  9. The presence of heteroscedasticity might be due to the fact that μ t is an estimated dependent variable (Lewis and Linzer 2005).

  10. We also investigated if either the “derivative effect” or the “level effect” is dominant, by standardizing the variables involved in (10)–(12). However, this exercise returned inconclusive results as in (10) the derivative effect is dominating, while in (11) and (12) the level effect has a greater coefficient in absolute value.

  11. Data on C4 were downloaded from http://www.census.gov/epcd/www/concentration.html and they were averaged over the period 1958–1992.

  12. The exceptions were the sectors whose SIC 4 digits codes were: 2273, 2371, 2391, 2392, 3161, 3262, 3263, 3911, 3914, 3915, 3931, 3942, 3944, 3949, 3961.

  13. Which can be downloaded from http://www.bea.gov/industry/io_benchmark.htm. We used the 1987 IO tables.

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Correspondence to Andrea Vaona.

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I would like to thank the attendants to my seminars held at the Kiel Institute for the World Economy and at the 16th International Conference on Panel Data held at the University of Amsterdam. I also wold like to thank two anonymous referee for insightful comments. The usual disclaimer applies.

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Vaona, A. A nonparametric panel data approach to the cyclical dynamics of price-cost margins in the fourth Kondratieff wave. Eurasian Bus Rev 6, 155–170 (2016). https://doi.org/10.1007/s40821-015-0034-0

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