Describing Firm's Behavior from Revenue and Cost Data
Open Access
- Author:
- DeSouza, Sergio
- Graduate Program:
- Economics
- Degree:
- Doctor of Philosophy
- Document Type:
- Dissertation
- Date of Defense:
- August 23, 2004
- Committee Members:
- James R. Tybout, Committee Chair/Co-Chair
Mark John Roberts, Committee Member
Susana Esteban, Committee Member
Spiro E Stefanou, Committee Member - Keywords:
- Industrial organization
econometrics
discret-choice models - Abstract:
- The main objective of this research is to discuss and extend the existing literature that is concerned with the estimation of demand and supply parameters to determine unobserved prices, quantities, quality and marginal costs at the firm-level using data sets that reports only revenue and cost figures. A common approach to estimate these parameters is given by the production function. However, to be implemented it needs output data, which most plant-level data sets do not report. In the second chapter (the first one is an introduction), using the same framework, I shall investigate the consequences of ignoring price heterogeneity on the markup estimates from the production function in plant or firm–levels studies. I show that ignoring output price heterogeneity yield markup estimates severely biased towards one regardless of competitiveness levels. I set up an econometric model that assumes monopolistic competition and a CES demand function in a differentiated product market that is easy to estimate and allows for the use aggregate instruments to improve on the OLS estimations. In the third chapter, I discuss the estimation of discrete-choice model of demand. Katayma, Lu and Tybout (2003) used a nested logit model to derive consumer and producer surplus to measure efficiency. Their work (KLT) however differentiates from the others since the data set used there is not quite informative. Again, it assumes that only revenue and total costs are observed. Then combining these data with demand and the quasi-supply relation they demonstrate how to estimate the parameters of interest. I demonstrate how to extend the KLT framework by including the extra information provided by aggregate data. Although it may be difficult to obtain detailed data on quantities at the plant level, the same is not true for aggregate variables. I consider two different hypotheses on the nature of this aggregate measure. The first one assumes that this information is noisy, while the second assumes that this information is deterministic and therefore error free. Each assumption yields a different estimation strategy with potentially yield different parameter estimates. With the preference parameters, qualities and marginal costs determined according to the methodology developed in the third chapter, one is able to construct consumer and producer welfare measures. The first two sections of the third chapter present counterfactual experiments. They consist on assuming exogenous changes in the market environment and analyzing the consequent welfare variation. The former simulation assumes a sharp price decrease in the imported good price. As expected, due to competitive pressures and consequent lower prices, consumer welfare goes up and producers’ profits go down. In turn, the second section simulates a regulatory action whose objective is to split up the existing monopoly owned by Bavaria S.A. After the break up, the company does not internalize the price decision of all domestic beers in the market, then prices go down and similar welfare effects take place. Finally, the last section discusses the construction of welfare-based price indices and the identification of intertemporal welfare variation.