THE IMPACT OF LABOR MARKET REGULATION ON EMPLOYMENT IN LOW‐INCOME COUNTRIES: A META‐ANALYSIS

Controversy over labor market policy often centers on achieving a balance between preventing worker exploitation, and avoiding loss of productivity or employment through excessive regulation. Although the literature documenting the impact of labor market regulation on employment is extensive, there is a dearth of evidence on the impact of such policies in low‐income countries (LICs). Since it is easier for workers, especially women, to slip into the informal sector in LICs, regulations are likely to have stronger impacts on formal employment in these countries (but lower impacts on unemployment). We systematically reviewed available research from countries that are, or were until recently, LICs. Most studies document that more stringent labor regulations are associated with lower formal sector employment and higher informal sector employment. We also conducted a metaregression analysis of the impact of minimum wages on formal and informal employment. After controlling for publication bias, higher minimum wages are associated with lower formal employment and a higher share of informal workers.     

The Impact of Agricultural Import Tariff on Economic Growth： Evidence From Mercosur Countries

This research paper attempts to determine the relationship between agricultural import tariff and economic growth of Mercosur countries over the period 1996-2007 using regression analysis as well as evaluates the gains and losses from the group＇s trade policy over the same period. The introductory part of this paper focuses on the dynamics of changes in economic growth, trade, and import tariff of these countries over the last two decades. The results of the performed regression analysis of panel data suggest that trade liberalization has a quantitatively significant positive effect on growth. By using the coefficient estimates on tariff, the authors perform a quantitative evaluation of gains and losses from trade policy, for which tariff measures to trade （imports） are used as a proxy.     

Self-employment of immigrants and natives in Sweden – a multilevel analysis

Recent research suggests that self-employment among immigrants is due to a combination of multiple situational, cultural and institutional factors, all acting together. Using multilevel regression and unique data on the entire population of Sweden for the year 2007, this study attempts to quantify the relative importance for the self-employed of embeddedness in ethnic contexts (country of birth) and regional business and public regulatory frameworks (labour market areas). This information indicates whether the layers under consideration are valid constructs of the surroundings that influence individual self-employment. The results show that 10% (women) and 8% (men) of the total variation in individual differences in self-employment can be attributed to the country of birth. When labour market areas are included in the analyses, the share of the total variation increases to 14% for women and 12% for men. The results show that the ethnic context and the economic environment play a minor role in understanding individual differences in self-employment levels. The results can have important implications when planning interventions or other actions focusing on self-employment as public measures to promote self-employment often are based on geographic areas and ethnic contexts.     

Improving Agricultural Physical Marketing Infrastructure in Africa Through More Self-Help

The paper provides a brief overview of the problems of physical agricultural marketing infrastructure in Africa, with particular reference to rural roads and marketing facilities, such as storage, processing and market centres. In order to overcome these constraints, it is necessav to strengthen macro policy changes, with particular reference to commodity marketing, rural finance and government decentralization policies with the obiective of providing more incentives to marketing enterprises and local authorities to promote infrastructure development. Changes in macro policies have to be supported by adequate training programmes, support to institution building and adjustment of aid strategies to encourage self-help in developing marketing infrastructure.     

Spatial modelling of claim frequency and claim size in non-life insurance

In this paper, models for claim frequency and average claim size in non-life insurance are considered. Both covariates and spatial random effects are included allowing the modelling of a spatial dependency pattern. We assume a Poisson model for the number of claims, while claim size is modelled using a Gamma distribution. However, in contrast to the usual compound Poisson model, we allow for dependencies between claim size and claim frequency. A fully Bayesian approach is followed, parameters are estimated using Markov Chain Monte Carlo (MCMC). The issue of model comparison is thoroughly addressed. Besides the deviance information criterion and the predictive model choice criterion, we suggest the use of proper scoring rules based on the posterior predictive distribution for comparing models. We give an application to a comprehensive data set from a German car insurance company. The inclusion of spatial effects significantly improves the models for both claim frequency and claim size, and also leads to more accurate predictions of the total claim sizes. Further, we detect significant dependencies between the number of claims and claim size. Both spatial and number of claims effects are interpreted and quantified from an actuarial point of view.     

Excel与SPSS在线性回归预测中的比较分析

线性回归分析是经济管理与预测的一个重要的量化分析方法。分别运用Excel与SPSS对同一实际问题进行线性回归分析,得出两种软件在线性回归预测问题上各有其优势,在经济管理的实际应用中无论选择那种软件都要了解其功能和操作的特点,有助于对实际问题恰当而且正确地分析与预测。     

Remark on a theorem by Gurland

Abstract

Let X ₁,X ₂,...,X _n be a random sample of size from a distribution with probability density function p(x|θ), where the unknown parameter θ belongs to a non-degenerate interval I. The unknown true value of θ will be denoted by θ₀.     

HEDONIC PRICE INDEXES FOR RESIDENTIAL HOUSING: A SURVEY,EVALUATION AND TAXONOMY

Every house is different. It is important that house price indexes take account of these quality differences. Hedonic methods which express house prices as a function of a vector of characteristics (such as number of bedrooms and bathrooms, land area and location) are particularly useful for this purpose. I consider here some developments in the hedonic methodology, as it is applied in a housing context, that have occurred in the last three decades. A number of hedonic house price indexes are now available. However, it is often difficult to see how these indexes relate to each other. For this reason I attempt to impose some structure on the literature by developing a taxonomy of hedonic indexes, and then show how existing indexes fit into this taxonomy. Also discussed are some promising areas for future research in the hedonic field. In particular, greater use needs to be made of spatial econometric and nonparametric methods to exploit the increased availability of geospatial data. The main criticisms of the hedonic approach are evaluated and compared with those of the repeat‐sales and stratified median methods. The overall conclusion is that the advantages of the hedonic approach outweigh its disadvantages.     

Exploring the effect of diversification strategy on R&D intensity using quantile regression: evidence from France

This study examines the relationship between firm diversification strategy and R&D intensity for a sample of large French companies between 2008 and 2012. Applying quantile regression, we provide evidence that the choice of diversification affects R&D intensity in a differentiated way. The results indicate that a low level of diversification (below the twentieth quantile) has no significant impact on R&D intensity. Conversely, a moderate or high level of diversification has a negative and significant impact on R&D intensity. These findings suggest that R&D intensity seems to be significantly higher in related-business firms than in unrelated-business firms.     

Effect of driver,roadway, collision,and vehicle characteristics on crash severity: a conditional logistic regression approach

The aim of the study is to examine the factors that appear to have a higher potential for serious injury or death of drivers in traffic accidents in Turkey, such as collision type, roadway surface, vehicle speed, alcohol/drug use, and restraint use. Driver crash severity is the dependent variable of this study with two categories, fatal and non-fatal. Due to the binary nature of the dependent variable, a conditional logistic regression analysis was found suitable. Of the 16 independent variables obtained from Turkish police accident reports, 11 variables were found most significantly associated with driver crash severity. They are age, education level, restraint use, roadway condition, roadway type, time of day, collision location, collision type, number and direction of vehicles, vehicle speed, and alcohol/drug use. This study found that belted drivers aged 18–25 years involving two vehicles travelling in the same direction, in an urban area, during the daytime, and on an avenue or a street have better chances of survival in traffic accidents.