Mika Kortelainen

Measuring Eco‐efficiency of Production with Data Envelopment Analysis

Aggregation of environmental pressures into a single environmental damage index is a major challenge of eco‐efficiency measurement. This article examines how the data envelopment analysis (DEA) method can be adapted for this purpose. DEA accounts for substitution possibilities between different natural resources and emissions and does not require subjective judgment about the weights. Although DEA does not require subjective or normative judgment, soft weight restrictions can be incorporated into the framework. The proposed approach is illustrated by an application to assessing ecoefficiency of road transportation in the three largest towns of eastern Finland.

Costs and Efficiency of Higher Education Institutions in England: A DEA Analysis

As student numbers in higher education in the UK have expanded during recent years, it has become increasingly important to understand its cost structure. This study applies Data Envelopment Analysis (DEA) to higher education institutions in England to assess their cost structure, efficiency and productivity. The paper complements an earlier study that used parametric methods to analyse the same panel data. Interestingly, DEA provides estimates of subject-specific unit costs that are in the same ballpark as those provided by the parametric methods. The paper then extends the previous analysis and finds that further student number increases of the order of 20–27% are feasible through exploiting operating and scale efficiency gains and also adjusting student mix. Finally the paper uses a Malmquist index approach to assess productivity change in the UK higher education. The results reveal that for a majority of institutions productivity has actually decreased during the study period.

Firm and industry level profit efficiency analysis using absolute and uniform shadow prices

We discuss the nonparametric approach to profit efficiency analysis at the firm and industry levels in the absence of complete price information. Two new insights are developed. First, we measure profit inefficiency in monetary terms using absolute shadow prices. Second, we evaluate all firms using the same input-output prices. This allows us to aggregate firm-level profit inefficiencies to the overall industry inefficiency. Besides the measurement of profit losses, the presented approach enables one to recover absolute price information from quantity data. We conduct a series of Monte Carlo simulations to study the performance of the proposed approach in controlled production environments.

Stochastic Nonparametric Envelopment of Data: Cross-Sectional Frontier Estimation Subject to Shape Constraints

The field of production frontier estimation is divided between the parametric Stochastic Frontier Analysis (SFA) and the deterministic, nonparametric Data Envelopment Analysis (DEA). This paper explores an amalgam of DEA and SFA that melds a nonparametric frontier with a stochastic composite error. Our model imposes the standard SFA assumptions for the inefficiency and noise terms. The frontier is estimated nonparametrically, imposing monotonicity and convexity as in DEA. For estimation, we propose two alternative methods based on shape constrained nonparametric least squares. The performance of the proposed estimation techniques is examined using Monte Carlo simulations and an illustrative application.

Effects of Carbon Reduction Labels: Evidence from Scanner Data

We investigate the effects of carbon reduction labels using a detailed scanner data set. Using a difference-in-differences estimation strategy, we find that having a carbon label has no impact on detergent prices or demand. We also investigate possible heterogeneous effects of carbon labels using the synthetic control method. We find no evidence to indicate that the prices for the counterfactual detergents without the label would have been any different from the prices of the carbon-labeled detergents. We investigate the reasons for these results and conclude that the specific design of the carbon label is responsible for its lack of success.

Do Urban Neighborhoods Benefit from Homeowners? Evidence from Housing Prices

Homeownership is heavily subsidized in most countries. The adverse effects of this policy on economic efficiency and income distribution are well documented in the economics literature. The main argument in favor of subsidizing homeownership is that it creates positive externalities that offset these adverse effects. In this paper, we test whether homeowners create positive externalities that capitalize into housing prices in multi�?story buildings. Using semi�?parametric hedonic regressions with and without instrumental variables, we find no evidence of positive externalities, although the results with instrumental variables are somewhat imprecise. This result is robust to several sensitivity checks and to a relaxation of the identification assumptions of our instrument using set identification.

Performance of Finnish dairy farms and its determinants: A comparison of parametric, semiparametric, and nonparametric methods

Abstract The aim of this article is to assess the efficiency improvement potential of Finnish dairy farms and to explain performance differences between farms using alternative production frontier methods. In our empirical analysis, we employ parametric, semiparametric, and fully nonparametric production frontier techniques to investigate differences between methodologies and to guarantee that the empirical results are not sensitive to the specific method used. Although we find marked differences in average efficiency with respect to alternative frontier techniques, the correlation of efficiency scores between methods is high, indicating that the order is fairly consistent. With regard to the determinants of performance differences, all the methods used provide fairly similar results concerning the influential factors. The results suggest that farms located in the north were significantly less efficient compared to farms in southern Finland. As the milk yield per cow is increased, efficiency scores increase on average, but stagnate or start to fall again at the highest levels of average milk yields.