Owner-Occupied Housing and the Composition of the Household Portfolio: The Case of France

This paper investigates the impact of housing demand on the composition of the optimal portfolios of homeowners in France, following the methodology developed by Flavin and Yamashita (NBER Working Paper 6389, 2002). We use historical data on housing prices and financial assets returns to estimate the mean return and covariance matrix of a set of assets including housing. We then calculate mean-variance efficient frontiers associated to various levels of the housing-to-net wealth ratio, corresponding to the average ratios observed for different age groups in the 1998 French Wealth Survey sample. Our numerical results fit the average portfolios in different age brackets quite well. Also, returns of housing and its covariance with the other assets indicate there is room in France for housing price derivatives.     

Stochastic Frontiers and Asymmetric Information Models

This article is an attempt to shed light on the specification and identification of inefficiency in stochastic frontiers. We consider the case of a regulated firm or industry. Applying a simple principal-agent framework that accounts for informational asymmetries to this context, we derive the associated production and cost frontiers. Noticeably this approach yields a decomposition of inefficiency into two components: The first component is a pure random term while the second component depends on the unobservable actions taken by the agent (the firm). This result provides a theoretical foundation to the usual specification applied in the literature on stochastic frontiers. An application to a panel data set of French urban transport networks serves as an illustration.     

Technical efficiency measures for dairy farms using panel data: A comparison of alternative model specifications

This article examines the impact of fixed effects production functions vis-à-vis stochastic production frontiers on technical efficiency measures. An unbalanced panel consisting of 96 Vermont dairy farmers for the 1971–1984 period was used in the analysis. The models examined incorporated both time-variant and time-invariant technical efficiency. The major source of variation in efficiency levels across models stemmed from the assumption made concerning the distribution of the one-sided term in the stochastic frontiers. In general, the fixed effects technique was found superior to the stochastic production frontier methodology. Despite the fact that the results of various statistical tests revealed the superiority of some specifications over others, the overall conclusion of the study is that the efficiency analysis was fairly consistent throughout all the models considered.     

DEA, DFA and SFA: A comparison

The nonparametric data envelopment analysis (DEA) model has become increasingly popular in the analysis of productive efficiency, and the number of empirical applications is now very large. Recent theoretical and mathematical research has also contributed to a deeper understanding of the seemingly simple but inherently complex DEA model. Less effort has, however, been directed toward comparisons between DEA and other competing efficiency analysis models. This paper undertakes a comparison of the DEA, the deterministic parametric (DFA), and the stochastic frontier (SFA) models. Efficiency comparisons across models in the above categories are done based on 15 Colombian cement plants observed during 1968–1988.     

Efficiency Measurement With Unbalanced Panel Data: Evidence from Tunisian Textile,Clothing and Leather Industries

This paper is concerned with the estimation of stochastic frontier production functions with unbalanced panel data when unobservable firm efficiency levels are related to explanatory variables. We use the weighted-means Instrumental Variables method acknowledged to R. Gardner (1998) which is a modification of the Hausman-Taylor (1981) procedure adapted for unbalanced panel data. The estimation method is used to examine technical efficiency in Tunisian textile, clothing and leather (TCL) industries during the period 1983–1994. Further, we assume a Translog production frontier where input uses are expressed in efficiency units and adjusted for the age of capital and types of labor. Firm-specific time-invariant technical efficiency is obtained using Schmidt and Sickles (1984) approach. The results suggest that the Instrumental Variables method produces more accurate estimates of the unknown firm level technical efficency. Mean efficency scores resulting from the MHT method is of 66.5%.     

Misspecification Preferred: The Sensitivity of Inefficiency Rankings

Ruggiero (European Journal of Operational Research 115, 555–563. 1999) compared the two popular parametric frontier methods for cross-sectional data—the stochastic frontier and the corrected OLS—in a simulation study. He demonstrated that the inefficiency ranking accuracy of the established stochastic frontier is uniformly inferior to that of the misspecified Corrected OLS (COLS) (which lacks an error term). The reason for his result remains unclear, however. In this paper, a more extensive simulation study is therefore conducted to find out whether the superiority of COLS is simply due to small sample sizes or to poor performance of the inefficiency level estimator.JEL Classification: C1,C2,C5     

Technical Change and Efficiency in Turkish Manufacturing Industries

Technical progress and production efficiency are central to economic growth and international competitiveness. However, these topics received little attention in Less Developed Countries. This study is the first attempt to measure and to understand the extent and importance of technical progress and efficiency in Turkish manufacturing industries. Stochastic production frontiers for Turkish textile, cement, and motor vehicles industries are estimated by using panel data of plants for the years 1987 to 1992. The rate and direction of technical change for each industry are estimated by introducing time-dependent variables in the production function. Sector-specific factors which influence technical efficiency of manufacturing plants are also identified.     

ICT Investment, Productivity and Efficiency: Evidence at Firm Level Using a Stochastic Frontier Approach

We analyze the determinants of ICT investment and the impact of information technology on productivity and efficiency on a representative sample of small and medium sized Italian firms. In order to test the most relevant theoretical predictions from the ICT literature we evaluate the impact of investment in software, hardware and telecommunications of these firms on a series of intermediate variables and on productivity. Among intermediate variables we consider the demand for skilled workers, the introduction of new products and processes and the rate of capacity utilization. Among productivity measures we include total factor productivity, the productivity of labor, and the distance from the best practice by using a stochastic frontier approach. Our results show that the effect of ICT investment on firm efficiency can be more clearly detected at firm level data by decomposing it into software and telecommunications investment. We find that telecommunications investment positively affects the creation of new products and processes, while software investment increases the demand for skilled workers, average labor productivity and proximity to the optimal production frontier. We interpret these results by arguing that ICT investment modifies the trade-off between scale and scope economies. While software investment increases the scale of firm operations, telecommunications investment creates a flexibility option easing the switch from a Fordist to a flexible network productive model in which products and processes are more frequently adapted to satisfy consumers taste for variety.     

One-Step and Two-Step Estimation of the Effects of Exogenous Variables on Technical Efficiency Levels

Consider a stochastic frontier model with one-sided inefficiency u, and suppose that the scale of u depends on some variables (firm characteristics) z. A one-step model specifies both the stochastic frontier and the way in which u depends on z, and can be estimated in a single step, for example by maximum likelihood. This is in contrast to a two-step procedure, where the first step is to estimate a standard stochastic frontier model, and the second step is to estimate the relationship between (estimated) u and z.In this paper we propose a class of one-step models based on the scaling property that u equals a function of z times a one-sided error u ^* whose distribution does not depend on z. We explain theoretically why two-step procedures are biased, and we present Monte Carlo evidence showing that the bias can be very severe. This evidence argues strongly for one-step models whenever one is interested in the effects of firm characteristics on efficiency levels.     

Post-crisis regulatory reforms and bank performance: lessons from Asia

Based on a large dataset from eight Asian economies, we test the impact of post-crisis regulatory reforms on the performance of depository institutions in countries at different levels of financial development. We allow for technological heterogeneity and estimate a set of country-level stochastic cost frontiers followed by a deterministic bootstrapped meta-frontier to evaluate cost efficiency and cost technology. Our results support the view that liberalization policies have a positive impact on bank performance, while the reverse is true for prudential regulation policies. The removal of activities restrictions, bank privatization and foreign bank entry has a positive and significant impact on technological progress and cost efficiency. In contrast, prudential policies, which aim to protect the banking sector from excessive risk-taking, tend to adversely affect banks’ cost efficiency but not cost technology.