Abstract
By understanding how productivity shocks affect firm value, an entrepreneur can better compute the risk premium associated with uncertainty in production. This study explores the link between plant-level productivity and firm value for the baking and confectionary sector. From the impulse response analysis, the study finds that there is a lag in the firm’s response to productivity shocks at the plant level. Further, the paper employs Tobin’s Q as a valuation metric that acts as a link between a firm’s manufacturing plant productivity and firm value. Empirical estimations indicate that there is comovement between firm valuation and plant level productivity.
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Notes
In this study, we examine plant level data and firm data for the following 4 digit SIC sectors. The sectors corresponding to each SIC are indicated in the parentheses: 2051 (bread and cake related products), 2052 (cookies and crackers), 2064 (candy and confectionary products), 2066 (chocolates and cocoa products) and 2067 (chewing gum).
Eric J. Bartelsman, Randy A. Becker, and Wayne B. Gray’s (2000) NBER-CES Manufacturing Industry Database include annual industry-level data on output, employment, payroll and other input costs, investment, capital stocks, TFP, and various industry-specific price indexes. The authors acknowledge data help from Randy Becker of the US Census Bureau.
The following variables are computed as follows:
$$ C = \ln \left( {\frac{\text{Total Cost}}{{P_M }}} \right),K = \ln \left( {\frac{{P_K }}{{P_M }}} \right),L = \left( {\frac{{P_L }}{{P_M }}} \right),E = \ln \left( {\frac{{P_E }}{{P_M }}} \right){\text{ and Y = }}\left( {\text{ln Y}} \right) $$In general, when we include time trends in our models we are making implicit assumptions about the nature of technological change. If we take the derivative of C with respect to T:
$$ \frac{{\partial C}}{{\partial T}} = \psi_K K + \psi_L L + \psi_E E + \lambda_{YT} Y + \eta_T $$our specification implicitly assumes that the technological change effect is directly related to input usage, relative price of inputs and output. In terms of estimation, η T is a constant, thus impacting the intercept term while \( \psi_K, \psi_L, \psi_E \) are slope parameters. In general, we have introduced the time trend into our model based on our thoughts on how technological developments might affect the confectionary and bakery industry. In general, the time trend should reflect industry specific technological change and developments. This in turn impacts the optimizing economic behavior.
Detailed results are available upon request from the authors.
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We gratefully acknowledge and thank Harihara Baskaran and the anonymous reviewer for their helpful comments and suggestions.
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Balasubramanyan, L., Mohan, R. How well is productivity being priced?. J Econ Finan 34, 415–429 (2010). https://doi.org/10.1007/s12197-009-9083-5
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DOI: https://doi.org/10.1007/s12197-009-9083-5