The directional profit efficiency measure: on why profit inefficiency is either technical or allocative

The directional distance function encompasses Shephard’s input and output distance functions and also allows nonradial projections of the assessed firm onto the frontier of the technology in a preassigned direction. However, the criteria underlying the choice of its associated directional vector are numerous. When market prices are observed and firms have a profit maximizing behavior, it seems natural to choose as the directional vector that projecting inefficient firms towards profit maximizing benchmarks. Based on that choice of directional vector, we introduce the directional profit efficiency measure and show that, in this general setting, profit inefficiency can be categorized as either technical, for firms situated within the interior of the technology, or allocative, for firms lying on the frontier. We implement and illustrate the analytical model by way of Data Envelopment Analysis techniques, and introduce the necessary optimization programs for profit inefficiency measurement.     

Modeling CRS bounded additive DEA models and characterizing their Pareto-efficient points

Dealing with weighted additive models in Data Envelopment Analysis guarantees that any projection of an inefficient unit belongs to the strong efficient frontier, among other interesting properties. Recently, constant returns to scale (CRS) range-bounded models have been introduced for defining a new additive-type efficiency measure (see Cooper et al. in J Prod Anal 35(2):85–94, 2011). This paper continues such earlier work further, considering a more general setting. In particular, we show that under free disposability of inputs and outputs, CRS bounded additive models require a double set of slacks. The second set of slacks allows us to properly characterize all the Pareto-efficient points associated to the bounded technology. We further introduce the CRS partially-bounded additive models.     

Bank lending,misleading signals,and the latin american debt crisis

This article explores the microfoundations of bank and borrower behavior in the Latin American debt crisis. In the model developed, less developed countries attract loans by signaling their ability and willingness to pay. Some of the signals are “coercive” because they indicate that if income targets are not met, income will be redistributed in order to honor debt obligations. Implicit in such coercive signaling is the borrower's expectation that redistribution will not damage economic productivity. A coercive signal is misleading when feedback effects on social stability and work effort—and thus on the ability to pay—are underestimated or ignored; in this case, it inaccurately predicts repayment prospects. We estimate two equations: (1) private lending to Latin borrowers as a function of our specified signals, and (2) the probability of payments problem as a function of the same set of signals. The results support our borrowing model: coercive signals do enhance lending, and at least one of these signals is misleading.     

Circularity of the Malmquist productivity index

The geometric mean version of the Malmquist productivity index does not satisfy the circular test, and its component adjacent period indexes can give different productivity change measures for the same data. A fixed-base version of the index solves both problems, but it is not independent of the base period. It has been argued that time-neutrality of technical change is necessary and sufficient for all three properties to hold. We show that time-neutrality is sufficient, but not necessary, for all three properties. We develop a weaker version of time-neutrality that is necessary and sufficient for all three properties to hold. We thank a very perceptive referee for helpful comments, although content remains our responsibility. A longer working paper is available on request.     

Relating Macro-economic Efficiency to Financial Efficiency: A Comparison of Fifteen OECD Countries Over an Eighteen Year Period

This paper examines the role of the banking sector in the overall economic activity and its contribution to the convergence/divergence in fifteen OECD countries over the time period of 1980–1997. We resort to a non-parametric technique (DEA) and estimate a world wide macro-economic as well as a worldwide banking frontier. We find a very similar pattern in the evolution of banking and macro-economic efficiency. We further study the evolution of the macro-economic and banking productivity and discover, in both cases, convergence over time. Our first finding is that the performance of the banking sector helps to explain the overall economic performance. Our second finding is that the financial orientation of each country constitutes a relevant feature for the last mentioned explanation.     

Franchising in Europe: Exploring the Case of Spain with Self‐organizing Time Maps

Economic crises affect both the organizational side and the brand side of the franchise. Using self‐organizing time maps, this study examines how franchise brand behavior influences decisions by potential franchisees in Spain. The findings confirm that franchising offers an alternative to the business turnaround strategy, which firms apply when faced with adverse changes in the environment such as those caused by the economic crisis in Spain. Results show that all franchise brands within the same sector behaved similarly, except for brands in the catering sector, which displayed varying responses to the economic changes. The authors discuss the implications of these results for future franchisees.     

PERMANENT INCOME, CONVERGENCE AND INEQUALITY AMONG COUNTRIES

The literature on inequality has generally focused on the analysis of annual per capita income. This paper adopts a different approach by considering the life-cycle dimension of inequality and convergence between economies from 1960 to 2000. We analyze the present value of the set of incomes individuals obtain throughout their whole life (permanent income). On the basis of this approach, various simulations are made to determine the effect on inequality in permanent income of variables such as survival rates and the long-run growth rates in current income. The results indicate that survival rates are an important source of inequality. Inequality in permanent income is about one third higher than in current income. The implication of this finding is that if the whole life-cycle dimension is not considered, the level of inequality among economies is being underestimated.     

Forecasting crude oil price volatility

We use high-frequency intra-day realized volatility data to evaluate the relative forecasting performances of various models that are used commonly for forecasting the volatility of crude oil daily spot returns at multiple horizons. These models include the RiskMetrics, GARCH, asymmetric GARCH, fractional integrated GARCH and Markov switching GARCH models. We begin by implementing Carrasco, Hu, and Ploberger’s (2014) test for regime switching in the mean and variance of the GARCH(1, 1), and find overwhelming support for regime switching. We then perform a comprehensive out-of-sample forecasting performance evaluation using a battery of tests. We find that, under the MSE and QLIKE loss functions: (i) models with a Student’s t innovation are favored over those with a normal innovation; (ii) RiskMetrics and GARCH(1, 1) have good predictive accuracies at short forecast horizons, whereas EGARCH(1, 1) yields the most accurate forecasts at medium horizons; and (iii) the Markov switching GARCH shows a superior predictive accuracy at long horizons. These results are established by computing the equal predictive ability test of Diebold and Mariano (1995) and West (1996) and the model confidence set of Hansen, Lunde, and Nason (2011) over the entire evaluation sample. In addition, a comparison of the MSPE ratios computed using a rolling window suggests that the Markov switching GARCH model is better at predicting the volatility during periods of turmoil.