Victim or Victimizer: Firm Responses to Government Corruption

What is the relationship between government corruption and firm performance? To address this question, I conduct a review of articles published in the leading management journals on government‐business interactions pertaining to rent‐seeking activities and integrate findings from the fields of international business, social issues in management, public organization, institutional change, and corporate political activity. I find that while much empirical work corroborates the earlier findings suggesting a corrosive impact of government corruption on firm performance in general, management research also points to the heterogeneous impact of government corruption on individual firm performance, driven by the strategic activities conducted by firms in response to corruption. I propose an integrative model of firm strategy vis‐à‐vis corruption that predicts the activity choice of the firm as predicated by its organizational structure, political resources, industry regulation, and surrounding political and social institutions.     

Closed-skew normality in stochastic frontiers with individual effects and long/short-run efficiency

This paper considers the estimation of Kumbhakar et al. (J Prod Anal. doi:10.1007/s11123-012-0303-1, 2012) (KLH) four random components stochastic frontier (SF) model using MLE techniques. We derive the log-likelihood function of the model using results from the closed-skew normal distribution. Our Monte Carlo analysis shows that MLE is more efficient and less biased than the multi-step KLH estimator. Moreover, we obtain closed-form expressions for the posterior expected values of the random effects, used to estimate short-run and long-run (in)efficiency as well as random-firm effects. The model is general enough to nest most of the currently used panel SF models; hence, its appropriateness can be tested. This is exemplified by analyzing empirical results from three different applications.     

Correcting for the endogeneity of pro-environment behavioral choices in contingent valuation

In contingent valuation studies, observed behavioral choices often enter as independent variables in the willingness to pay function. However, these variables may be endogenously determined when the error term in the behavioral model is correlated with the error term in the willingness to pay model. We investigate the effects of correcting for the endogeneity of a variable, namely membership status in environmental organizations that proxies unobservable characteristics of the respondents. Jointly modeling the membership variable and the willingness to pay response yields an estimate for the effect of the former that contradicts previous findings but is intuitive and agrees with theoretical expectations.     

Threshold bipower variation and the impact of jumps on volatility forecasting

This study reconsiders the role of jumps for volatility forecasting by showing that jumps have a positive and mostly significant impact on future volatility. This result becomes apparent once volatility is separated into its continuous and discontinuous components using estimators which are not only consistent, but also scarcely plagued by small sample bias. With the aim of achieving this, we introduce the concept of threshold bipower variation, which is based on the joint use of bipower variation and threshold estimation. We show that its generalization (threshold multipower variation) admits a feasible central limit theorem in the presence of jumps and provides less biased estimates, with respect to the standard multipower variation, of the continuous quadratic variation in finite samples. We further provide a new test for jump detection which has substantially more power than tests based on multipower variation. Empirical analysis (on the S&P500 index, individual stocks and US bond yields) shows that the proposed techniques improve significantly the accuracy of volatility forecasts especially in periods following the occurrence of a jump.     

Trade Openness and Spatial Inequality in Emerging Countries

Abstract

Emerging world countries have experienced over the last two decades a significant change in their trade patterns. Bold trade reforms have been followed by rapid rises in international trade levels. However, despite these radical changes, we know remarkably little about how changes in trade patterns are affecting the evolution of regional inequality in the developing world. This paper addresses the link between trade openness and spatial inequality across 22 emerging countries over the period between 1990 and 2006. Our findings show that changes in international trade bring about a significant rise in within-country inequality across the developing world and that this impact is greatest in the poorest countries. This result is robust to the inclusion of a number of control variables, and to changes in the specification of the sample and in the measure used to quantify the level of regional disparities. Consequently, the increase in trade exposure across the emerging world, while possibly benefiting the countries involved in the process in aggregate terms, is generating winning and losing regions.     

Incremental costs associated with myocardial infarction and stroke in patients with type 2 diabetes mellitus: an overview for economic modeling

Objective:

To identify cost estimates related to myocardial infarction (MI) or stroke in patients with type 2 diabetes mellitus (T2DM) for use in economic models.

Methods:

A systematic literature review was conducted. Electronic databases and conference abstracts were screened against inclusion criteria, which included studies performed in patients who had T2DM before experiencing an MI or stroke. Primary cost studies and economic models were included. Costs were converted to 2012 pounds sterling.

Results:

Fifty-four studies were identified: 13 primary cost studies and 41 economic evaluations using secondary sources for complication costs. Primary studies provided costs from 10 countries. Estimates for a fatal event ranged from £2482–£5222 for MI and from £4900–£6694 for stroke. Costs for the year a non-fatal event occurred ranged from £5071–£29,249 for MI and from £5171–£38,732 for stroke. Annual follow-up costs ranged from £945–£1616 for an MI and from £4704–£12,926 for a stroke. Economic evaluations from 12 countries were identified, and costs of complications showed similar variability to the primary studies.

Discussion:

The costs identified within primary studies varied between and within countries. Many studies used costs estimated in studies not specific to patients with T2DM. Data gaps included a detailed breakdown of resource use, which affected the ability to compare data across countries.

Conclusions:

In the development of economic models for patients with T2DM, the use of accurate estimates of costs associated with MI and stroke is important. When country-specific costs are not available, clear justification for the choice of estimates should be provided.     

Elicitation of Expert Opinion in Benefit Transfer of Environmental Goods

Benefit transfer is a method for estimating the value of environmental goods that involves the use of past information on identical or similar goods. This paper considers the extent to which benefit transfer can be based on prior distributions elicited from expert opinion. We propose two alternative methods to elicit the parameters of a prior distribution from experts on environmental valuation. An experiment is carried out on the value of National Parks in Spain. The results from the elicited distributions are compared with the information provided by onsite samples of visitors. The results indicate that individual experts made different predictions about the potential value of the policy areas that were diverse and unable to accurately predict the value for each policy site. However, the average across the elicited distributions approaches the estimated distribution with empirical data and accurately predicts the relative values for the two policy sites considered.     

Single or double bounded contingent valuation? A Bayesian test

This paper evaluates the performance of asymptotic approximations of the Bayes factor to appraise the relative likelihoods of the bivariate and the restricted double bounded models for contingent valuation. The performance of the Bayes factor test is studied by Monte Carlo simulation showing that it correctly chooses the bivariate model when appropriate, but tends to over predict the double bounded model when the correlation coefficient is not estimated accurately. However, the quadratic error in estimating willingness to pay is reduced if the model preferred by the test is chosen. In addition, we consider the effect of averaging the estimates of WTP from both models, weighting each model with its posterior probability. The results show that ‘model averaging’ across the competing hypothesis further reduces the squared error. The applications with two data sets on National Parks show that the test rejects the restricted double bounded hypotheses against the bivariate model.