The Sources of Capital Misallocation

Abstract

We develop a methodology to disentangle sources of capital “mis-allocation,” i.e., dispersion in value-added/capital. It measures the contributions of technological/informational frictions and a rich class of firm-specific factors. An application to Chinese manufacturing firms reveals that adjustment costs and uncertainty, while significant, explain only a modest fraction of the dispersion, which stems largely from other factors: a component correlated with productivity and a fixed effect. Adjustment costs are more salient for large US firms, though other factors still account for the bulk of the dispersion. Technological/markup heterogeneity explains a limited fraction in China, but a potentially large share in the United States. (JEL D22, D24, D25, E22, G31, L60, O11, O14, O47, P31)

Firm Performance and Macro Forecast Accuracy

“…We also examined robustness against possible sampling selection effects by estimating the equation ( 9) by weighting observations by inverse of response rates and found similar results as in the main specification (Table A.6 in the Appendix show the results). 17 Also, we observe qualitatively the same results when we regress the growth rate of TFP (i.e. the first difference in the logarithm of TFP) instead of the level of TFP on absolute forecast errors (the estimated coefficient is -0.0037 and the standard error is 0.0012).…”

Resource misallocation and total factor productivity: Manufacturing firms in South Africa

“…This is equivalent to equation 20 inHsieh and Klenow (2009).4 David and Venkateswaran (2017) examine the extent to which capital misallocation can be attributed to adjustment costs or distortions. They find that adjustment costs play a modest role in China but are relatively important among large firms in the US.…”

Misallocation and aggregate productivity across time and space

“…This insight provides identification of the relative strength of distortions versus adjustment costs in the data. Using data for China and other countries, David and Venkateswaran (2017) find a larger role for distortions in poor economies. Third, inputs may be measured with error and the role of measurement error has now been studied by Bils et al (2017) using panel data.…”

“…In addition, with just crosssectional data, it is difficult to separate distortions from shocks in the presence of adjustment costs. David and Venkateswaran (2017) use annual panel data to identify the sources of dispersion in the marginal product of capital across producers. The key insight is that whereas distortions and adjustment costs can equally rationalize cross-sectional dispersion in marginal products, distortions and adjustment costs have different implications for the autocorrelation of investment.…”