Firm-Heterogeneity, Persistent and Transient Technical Inefficiency

This paper provides a new model that disentangles firm effects from persistent (time-invariant/long-term) and transient (time-varying/short-term) technical inefficiency.Bayesian analysis; Markov Chain Monte Carlo; Technical efficiency.

Does Deregulation Change Economic Behavior of Firms?

Cost minimization and profit maximization behavioral assumptions are most widely used in microeconomic theory to analyze firm behavior. However, in practice researchers do not know whether every firm in the sample maximizes profit or minimizes cost. In this paper we address this problem via a latent class modeling approach in which we first consider the cost minimization problem (first class) and then the profit maximization problem (second class). The two problems are then mixed and the probabilities of class membership are made functions of covariates. This approach does not require researchers to know which firms maximize profit and which ones minimize cost. On the contrary, it helps us to determine not only which firms behave like profit maximizers but also why and what differentiates them from firms that failed to maximize profit. The new technique is illustrated using a panel data for the US airlines. The empirical findings suggest that very few airlines maximize profit consistently (if at all) and that deregulation had a positive impact on the chances of behaving like profit maximizers, although very few airlines continue to maximize profit even after the deregulation.

Estimation of Technical and Allocative Inefficiencies in a Cost System: An Exact Maximum Likelihood Approach

Estimation and decomposition of overall (economic) efficiency into technical and allocative components goes back to Farrell (1957). However, in a cross-sectional framework joint econometric estimation of efficiency components has been mostly confined to restrictive production function models (such as the Cobb-Douglas). In this paper we implement a maximum likelihood (ML) procedure to estimate technical and allocative inefficiency using the dual cost system (cost function and the derivative conditions) in the presence of cross-sectional data. Specifically, the ML procedure is used to estimate simultaneously the translog cost system and cost increase due to both technical and allocative inefficiency. This solves the so-called ‘Greene problem’ in the efficiency literature. The proposed technique is applied to the Christensen and Greene (1976) data on U.S. electric utilities, and a cross-section of the Brynjolfsson and Hitt (2003) data on large U.S. firms.Technical inefficiency, allocative inefficiency, the Greene problem, translog cost function

Non-Sationarity in the Consumption-Income Ratio: Further Evidence from Panel and Assymetric Unit Root Tests

In this paper we test the stationarity properties of the consumption-income ratio for a sample of 14 European Union countries over the period 1960-1999 utilizing recent advances in panel unit root and asymmetric unit root tests. We find that a failure to take account of asymmetries, would imply I(1) consumption income ratio although unit root tests based on TAR models indicate stationarity in at least one regime. This result provides more evidence in relation to Sarantis and Stewart (Economics Letters, 1999) who found that the consumption-income ratio is I(1).Consumption-Income Ratio Panel Unit Root Tests Assymetric Unit Root Tests TAR Models

Efficiency measurement with nonstationary variables: an application of panel cointegration techniques

In this paper, we apply panel cointegration tests and estimation techniques to obtain efficiency measures when it is uncertain whether the underlying technological relationship is structural or spurious due to possible non-stationarity of the data. We illustrate the dangers of efficiency measurement with panel data when integration and cointegration are not taken into account. We apply these techniques to efficiency measurement in U.S. airlines and find striking differences compared to results obtained with the traditional approach.Cointegration

The joint estimation of bank-level market power and efficiency

The aim of this study is to provide a methodology for the joint estimation of efficiency and market power of individual banks. The proposed method utilizes the separate implications of the new empirical industrial organization and the stochastic frontier literatures and suggests identification using the local maximum likelihood (LML) technique. Through LML, estimation of market power of individual banks becomes feasible, while a number of restrictive theoretical and empirical assumptions are relaxed. The empirical analysis is carried out on the basis of EMU and US bank data and the results suggest small differences in the market power and efficiency levels of banks between the two samples. Market power estimates indicate fairly competitive conduct in general; however, heterogeneity in market power estimates is substantial across banks within each sample. The latter result suggests that while the banking industries examined are fairly competitive in general, the practice of some banks deviates from the average behavior, and this finding has important policy implications. Finally, efficiency and market power present a negative relationship, which is in line with the so-called “quiet life hypothesis”.Efficiency; market power; local maximum likelihood

New evidence on stylized facts of the business cycle: An International Investigation (1960-2004)

This paper investigates the business cycles in output and real output in nine countries. We detect the long-run and short-run relationships between the cyclical components of output and real output, using Autoregressive Distributed Lag and Error Correlation Models, respectively.

Bayesian analysis of multivariate stable distributions using one-dimensional projections

In this paper we take up Bayesian inference in general multivariate stable distributions. We exploit the representation of Matsui and Takemura (2009) for univariate projections, and the representation of the distributions in terms of their spectral measure. We present efficient MCMC schemes to perform the computations when the spectral measure is approximated discretely or, as we propose, by a normal distribution. Appropriate latent variables are introduced to implement MCMC. In relation to the discrete approximation, we propose efficient computational schemes based on the characteristic function