ALTERNATIVE ESTIMATING AND TESTING EMPIRICAL STRATEGIES FOR FRACTIONAL REGRESSION MODELS

Abstract In many economic settings, the variable of interest is often a fraction or a proportion, being defined only on the unit interval. The bounded nature of such variables and, in some cases, the possibility of nontrivial probability mass accumulating at one or both boundaries raise some interesting estimation and inference issues. In this paper we (i) provide a comprehensive survey of the main alternative models and estimation methods suitable to deal with fractional response variables, (ii) propose a full testing methodology to assess the validity of the assumptions required by each alternative estimator and (iii) examine the finite‐sample properties of most of the estimators and tests discussed through an extensive Monte Carlo study. An application concerning corporate capital structure choices is also provided.     

Outsourcing Operations in Project Management Offices: The Reality of Brazilian Companies

The purpose of this study is to explore the mechanisms that influence decisions regarding outsourcing competencies in the operation of project management offices (PMOs). The exploratory research described here involves the use of a web‐based survey for enterprises in Brazil. In 78 of the survey's valid cases, the PMO is operated using the organization's internal resources. A possible conclusion is that the PMO is unlikely to positively relate to the culture of external services used by the organization and to use outsourcing to operate the PMO.     

Maximum likelihood and restricted maximum likelihood estimation for a class of Gaussian Markov random fields

This work describes a Gaussian Markov random field model that includes several previously proposed models, and studies properties of its maximum likelihood (ML) and restricted maximum likelihood (REML) estimators in a special case. Specifically, for models where a particular relation holds between the regression and precision matrices of the model, we provide sufficient conditions for existence and uniqueness of ML and REML estimators of the covariance parameters, and provide a straightforward way to compute them. It is found that the ML estimator always exists while the REML estimator may not exist with positive probability. A numerical comparison suggests that for this model ML estimators of covariance parameters have, overall, better frequentist properties than REML estimators.     

The impact of exporting on firm productivity: a meta-analysis of the learning-by-exporting hypothesis

We conduct a meta-analysis of more than 30 papers that study the causal relationship between exporting and firm productivity. Our main result, robust to different specifications and to different weights for each observation, indicates that the impact of exporting upon productivity is higher for developing than developed economies. We also find that the export effect tends to be higher (1) in the first year that firms start exporting (compared to later years); and (2) when the sample used in the paper is not restricted to matched firms. Moreover, we find no evidence of publication bias.     

Market impact of international sporting and cultural events

We study market reaction to the announcements of the selected country hosting the Summer and Winter Olympic Games, the World Football Cup, the European Football Cup and World and Specialized Exhibitions. We generalize previous results analyzing a large number and different types of mega-events, evaluate the effects for winning and losing countries, investigate the determinants of the observed market reaction and control for the ex ante probability of a country being a successful bidder. Average abnormal returns measured at the announcement date and around the event are not significantly different from zero. Further, we find no evidence supporting that industries, that a priori were more likely to extract direct benefits from the event, observe positive significant effects. Yet, when we control for anticipation, the stock price reactions around the announcements are significant.     

Lending relationships in the interbank market

We use a unique dataset to show that relationships are an important determinant of banks' ability to access interbank market liquidity. More precisely, we find that: (i) banks with a larger reserve imbalance are more likely to borrow funds from banks with whom they have a relationship, and to pay a lower interest rate than otherwise; (ii) smaller banks and banks with more non-performing loans tend to have limited access to international markets, and rely more on relationships; (iii) relationships are established between banks with less correlated liquidity shocks. These results suggest that relationships allow banks to insure liquidity risk in the presence of market frictions such as transaction and information costs. Our analysis explicitly controls for the endogeneity of bank relationships.     

The Stability of Social Preferences in a Low‐Income Neighborhood

We investigate whether social preferences are stable across contexts using a field population of low‐income Americans. We develop and demonstrate a simplified, visually‐based experimental methodology appropriate for this population. We show that choices in a laboratory public goods game predict giving in real donation experiments, as well as self‐reported donations and volunteering outside the lab. At the same time, choices vary systematically by individual characteristics and decision context. Thus, our results provide evidence both for an underlying stable social preference and for the role of context in influencing the expression of that preference.     

Executive Compensation： Pay-for-Performance in High-Technology Firms

This study examines the relationship between corporate performance and the Chief Executive Officer （CEO） compensation in high-technology firms in the S＆P 500. The total short- and long-term CEO compensation in high-technology was compared with other industrial sectors from standard classification codes and tested in terms of corporate performance. The ExecuComp database was used to find the variables and to create a sample of firms between 2004 and 2010. Important corporate performance variables are used in this work, such as assets, employees, sales, net income, and earnings per share （EPS）, as reported by the firms for each year. A panel data GLS with a fixed effect model for time is estimated that describes total compensation for the period between 2004 and 2010. The result was aligned with the theory of executive compensations to address agency problems and to examine CEO pay-for-performance. The main objective of this paper is to consistently demonstrate that the performance is determined for the total CEO compensation for short- and long-term periods and to examine whether the total remunergttion paid to CEOs in high-technology firms in the S＆P 500 is related to corporate finance. This work provides a better understanding of the relationship between compensation and performance in high-technology firms. Results suggest that high-tech firms tend to use more sophisticated performance measurements to determine CEO compensation.