Search results

We searched JM from 1990 to 2005 to identify all studies that employed OLS regression.¹ The search resulted in 83 articles with 147 OLS regressions. Many authors specifically state that they used OLS and these were promptly included in the sample. Other authors acknowledged regression as a methodological procedure without explicitly specifying an estimation technique. To inquire whether OLS was used, we communicated with all of these authors. In all, 51 authors were contacted, with 44 responding. Of the 44 that responded 43 had used OLS; the only exception was subsequently excluded from the analysis. The remaining seven articles were checked once more, and consensus was reached that OLS had most likely been used. Therefore, they were also included in the study.

The purpose of the chapter is to test the hypothesis that food safety (chemical) standards act as barriers to international seafood imports. We use zero-accounting gravity models to test the hypothesis that food safety (chemical) standards act as barriers to international seafood imports. The chemical standards on which we focus include chloramphenicol required performance limit, oxytetracycline maximum residue limit, fluoro-quinolones maximum residue limit, and dichlorodiphenyltrichloroethane (DDT) pesticide residue limit. The study focuses on the three most important seafood markets: the European Union’s 15 members, Japan, and North America.Our empirical results confirm the hypothesis and are robust to the OLS as well as alternative zero-accounting gravity models such as the Heckman estimation and the Poisson family regressions. For the choice of the best model specification to account for zero trade and heteroskedastic issues, it is inconclusive to base on formal statistical tests; however, the Heckman sample selection and zero-inflated negative binomial (ZINB) models provide the most reliable parameter estimates based on the statistical tests, magnitude of coefficients, economic implications, and the literature findings. Our findings suggest that continually tightening of seafood safety standards has had a negative impact on exporting countries. Increasing the stringency of regulations by reducing analytical limits or maximum residue limits in seafood in developed countries has negative impacts on their bilateral seafood imports. The chapter furthers the literature on food safety standards on international trade. We show competing gravity model specifications and provide additional evidence that no one gravity model is superior.

Research on strategic choices available to the firm are often modeled as a limited number of possible decision outcomes and leads to a discrete limited dependent variable. A limited dependent variable can also arise when values of a continuous dependent variable are partially or wholly unobserved. This chapter discusses the methodological issues associated with such phenomena and the appropriate statistical methods developed to allow for consistent and efficient estimation of models that involve a limited dependent variable. The chapter also provides a road map for selecting the appropriate statistical technique and it offers guidelines for consistent interpretation and reporting of the statistical results.

This study examines the use of forecast combination to improve the accuracy of forecasts of cumulative demand. A forecast combination methodology based on least absolute value (LAV) regression analysis is developed and is applied to partially accumulated demand data from an actual manufacturing operation. The accuracy of the proposed model is compared with the accuracy of common alternative approaches that use partial demand data. Results indicate that the proposed methodology outperforms the alternative approaches.

This article surveys recent developments in the evaluation of point and density forecasts in the context of forecasts made by vector autoregressions. Specific emphasis is placed on highlighting those parts of the existing literature that are applicable to direct multistep forecasts and those parts that are applicable to iterated multistep forecasts. This literature includes advancements in the evaluation of forecasts in population (based on true, unknown model coefficients) and the evaluation of forecasts in the finite sample (based on estimated model coefficients). The article then examines in Monte Carlo experiments the finite-sample properties of some tests of equal forecast accuracy, focusing on the comparison of VAR forecasts to AR forecasts. These experiments show the tests to behave as should be expected given the theory. For example, using critical values obtained by bootstrap methods, tests of equal accuracy in population have empirical size about equal to nominal size.

In this paper we use a large linked employer-employee data set on German establishments between 1993 and 2012 to investigate how the gender composition of the top layer of management affects a variety of establishment and worker outcomes. We use two different measures to identify the gender composition of the top layer based on direct survey data: the fraction of women among top managers, and the fraction of women among working proprietors. We document the following facts: (a) There is a strong negative association between the fraction of women in the top layer of management and several establishment outcomes, among them business volume, investment, total wage bill per worker, total employment, and turnover; (b) Establishments with a high fraction of women in the top layer of management are more likely to implement female-friendly policies, such as providing childcare facilities or promoting and mentoring female junior staff; (c) The fraction of women in the top layer of management is also negatively associated with employment and wages, both male and female, full-time and part-time. However, all of these associations vanish when we include establishment fixed effects and establishment-specific time trends. This reveals a substantial sorting of female managers across establishments: small and less productive establishments that invest less, pay their employees lower wages, but are more female-friendly are more likely to be led by women.

Past research has shown that forecast combination typically improves demand forecast accuracy even when only two component forecasts are used; however, systematic bias in the component forecasts can reduce the effectiveness of combination. This study proposes a methodology for combining demand forecasts that are biased. Data from an actual manufacturing shop are used to develop the methodology and compare its accuracy with the accuracy of the standard approach of correcting for bias prior to combination. Results indicate that the proposed methodology outperforms the standard approach.

We model the conditions under which parents optimally reallocate time to childcare when an outside agent exogenously restricts the number of hours an employer can demand of a working parent. Theoretically, when the restriction binds, a parent's available time increases. We exploit a series of voluntary and mandated labor-market reforms in South Korea that regulated the statutory and maximum work hours of parents. The government implemented the laws in stages by industry and size of firms. This implementation process generates exogenous variation across families where one or both partners worked at jobs that were or were not affected by the reform. We show the reforms affected work hours and use the predicted changes to investigate the total amount they spent on paid childcare and whether or not they changed the relative use of market and parental care. When fathers get more time (work less), parents spend less money on childcare. A change in mother's work time does not affect expenditures. When parents get more time, they are more likely to spend money on paid childcare for school-age children and more likely to use private academies.

The basic model for estimating economic losses to a company that has some type of business interruption is well-documented in the forensic economics literature. A summary of much of this literature is contained in Gaughan (2000). The general method used to measure damages is essentially the same regardless of whether the loss occurs because of some type of natural disaster (as in insurance claims resulting from flood, fire, or hurricane) or whether it is caused by the actions of another party (as with potential tort claims). The interruption prevents the firm from selling units of product, which would otherwise have been supplied to the market. Economic damage is the loss of revenues less the incremental production costs of the units not sold, plus or minus some adjustment factors described in Gaughan (2000, 2004), and elsewhere.

The promotion of low tariffs and free trade has been the underlying driver of global economic growth. The recent political developments in the United States and Great Britain calls into question, whether free trade will be supported by the governments of the industrialized world in the future. Shortly after being inaugurated in 2017, the President of the United States has repeatedly announced his plans to impose punitive tariffs on the import of foreign products in order to protect the country’s domestic economy. Besides a controversial border adjustment tax, he has frequently brought up the possibility of imposing a 35% tariff on automobile imports. The chapter aims to analyze the effects of such a tariff on trade in the automotive sector between the United States and Germany as well as on German automobile manufacturers. It takes a quantitative approach to draw a conclusion about the relationship between import tariffs on automobiles and passenger vehicle imports from Germany to the United States utilizing a fixed effects regression model based on panel data. The model finds a significant negative correlation between the examined variables, but even in a worst case scenario, German manufacturers are resilient to the predicted revenue losses caused by a tariff increase.