基于技术含量的进出口商品贸易条件的影响因素研究

随着技术创新在对外贸易领域的作用日渐突出,出口商品的技术含量对一国贸易比较优势的转变、对外贸易的转型及商品外部竞争力的提高越发重要.基于此,本文以商品显示技术附加值作为判别技术含量差异的方式,对进出口商品进行分类并测算其贸易条件指数,借助分位数回归模型分析不同因素对各分类商品贸易条件的影响效应,发现尽管我国当前的比较优势商品仍集中在资源型、中技术产品领域,但高技术产品的贸易条件改善力度最大.同时,经济水平、税收等因素对不同技术含量商品贸易条件的影响表现出较大的差异,且当贸易条件处于不同分位水平时同一影响因素的作用系数也表现出明显的差别.     

基于半参数分位数回归模型的服务业发展水平影响因素研究

利用2020年全国329个地级市相关统计数据,建立半参数分位数回归模型,研究地区经济发展水平、城镇化率、政府作用、收入水平对不同发展水平的服务业影响效应。研究表明：地区经济发展水平与收入水平对各层次服务业发展均具有显著正向作用,但收入水平的促进作用会随着服务业发展水平的提高而减弱;城镇化率处于65%～80%时,对服务业具有逐步增强的促进作用;政府作用在促进服务业增长方面促进作用较弱。     

农户家庭生产要素配置与耕地抛荒的关系研究

在两部门模型框架下剖析耕地抛荒的微观因素,包括劳动力因素、收入因素与耕地因素;以实地调研数据为基础,结合分位数回归检验微观因素对耕地抛荒的影响程度。研究结果表明：在耕地抛荒严重的情况下,对耕地抛荒存在推动作用的因素包括农业劳动力的教育程度,非农劳动力的年龄与数量,非农收入比重与耕地面积;存在抑制作用的因素包括农业劳动力的年龄、数量与农业产出。     

金融发展差异扩大了城乡居民收入差距吗？

基于中国1981—2011年的样本数据,借助分位数回归方法考察城乡金融发展规模和效率差异以及其他主要因素对城乡收入差距的影响,结果表明：在各分位点上,城乡固定资产投资差异对城乡收入差距的影响均最强,劳动生产率差异次之,金融发展规模和效率差异最弱。因此,金融发展规模和效率差异并不是我国当前城乡收入差距扩大的主要因素,而固定资产投资和劳动生产率的城乡差异才是其主要成因。当城乡收入差距处于高分位点时,金融规模和效率差异的影响均不显著;当处于中间分位点时,金融效率差异对城乡收入差距有显著负影响;当处于低分位点时,金融规模差异对城乡收入差距有显著正影响。因此,缩小我国城乡收入差距,应根据城乡收入差距本身所处的不同分位数水平采取差异化策略。     

Economic uncertainty and corruption: evidence from a large cross-country data set

A vast amount of research has considered numerous causes and correlates of corruption. Also, there have been many studies of the consequences of various forms of uncertainty. However, exploration of the nexus between economic uncertainty and corruption appears scarce. After providing an intuitive and heuristic linkage between general economic uncertainty and corruption, this article uses a large cross-country data set to augment a fairly standard model with simple proxies for uncertainty and to investigate how economic uncertainty might affect the prevalence of corruption. In addition, a quantile-regression framework is used to judge how the strength of various covariates may differ with the level of corruption. Seven main points emerge from the estimates. First, economic uncertainty is associated positively with corruption, and the relation seems to be robust across measures of uncertainty and corruption. Second, quantile-regression estimates indicate considerable parametric heterogeneity across the distribution of corruption. Third, Gross Domestic Product (GDP) per capita has the expected corruption-mitigating role. Fourth, increased political rights and civil liberties also appear to lower corruption. Fifth, greater government consumption is associated with lower corruption. Sixth, while the hyperinflation dummy lacks significance in most OLS regressions, its significance varies across the distribution of corruption. Seventh, neither police force nor government subsidies shows significance, but transition economies have more corruption.     

Export Intensity and Plant Characteristics: What Can We Learn from Quantile Regression?

Using quantile regression and a rich cross section data set for German manufacturing plants this paper documents that the impact of plant characteristics on export activities varies along the conditional size distribution of the export/sales ratio. For example, firm size is statistically significant at a conventional level for the 0.25 quantile only; branch plant status matters at the upper tail of the conditional distribution of the export/sales ratio only; the craft shop dummy is only significant for the very top quantile; and patents do not matter at the very lower end of the conditional distribution of export over sales. This has implications both for understanding what makes a successful exporter, and for the design of policy measures with a focus on supporting exporters. JEL no. F10, D21, L60     

Value-at-Risk Prediction: A Comparison of Alternative Strategies

Given the growing need for managing financial risk, risk predictionplays an increasing role in banking and finance. In this studywe compare the out-of-sample performance of existing methodsand some new models for predicting value-at-risk (VaR) in aunivariate context. Using more than 30 years of the daily returndata on the NASDAQ Composite Index, we find that most approachesperform inadequately, although several models are acceptableunder current regulatory assessment rules for model adequacy.A hybrid method, combining a heavy-tailed generalized autoregressiveconditionally heteroskedastic (GARCH) filter with an extremevalue theory-based approach, performs best overall, closelyfollowed by a variant on a filtered historical simulation, anda new model based on heteroskedastic mixture distributions.Conditional autoregressive VaR (CAViaR) models perform inadequately,though an extension to a particular CAViaR model is shown tooutperform the others.     

Sectoral Differences in Plant Start-up Size in the Finnish Economy

New knowledge on the factors behind the choice of plant entry scale is important for understanding the entry process and the recruitment decisions of new plants in different sectors of the economy. The purpose of this paper is to evaluate the effect of various industry attributes on plant start-up size, measured with employment, using data on the entire Finnish business sector. The paper extends previous research by examining the differences between manufacturing and services and by using a richer set of explanatory variables. The relative importance of the covariates for different-sized entrants is taken into account by using a quantile regression approach. The results for manufacturing and services are remarkably similar. However, the findings imply that in the future analysis it is also important to consider the effect of the regional availability of educated and experienced work force on plant start-up size in these two sectors. The findings on the importance of scale economies and industry turbulence in determining start-up size correspond to the earlier studies. The results also show that single plant and multiplant entrants face a rather different entry environment. In addition, the employment share of foreign-owned entrants in the industry has to be taken into account.     

Regression Revisited

Sir Francis Galton introduced median regression and the use of the quantile function to describe distributions. Very early on the tradition moved to mean regression and the universal use of the Normal distribution, either as the natural ‘error’ distribution or as one forced by transformation. Though the introduction of ‘quantile regression’ refocused attention on the shape of the variability about the line, it uses nonparametric approaches and so ignores the actual distribution of the ‘error’ term. This paper seeks to show how Galton's approach enables the complete regression model, deterministic and stochastic elements, to be modelled, fitted and investigated. The emphasis is on the range of models that can be used for the stochastic element. It is noted that as the deterministic terms can be built up from components, so to, using quantile functions, can the stochastic element. The model may thus be treated in both modelling and fitting as a unity. Some evidence is presented to justify the use of a much wider range of distributional models than is usually considered and to emphasize their flexibility in extending regression models.     

A two-state analysis of estate taxes and charitable bequests from the most generous decedents

This study uses Censored Quantile Regression (CQR) and probate records for the years 2000–2005 to analyze charitable bequests of the most generous decedents from two states, Virginia and Louisiana. We focus on the most generous decedents because they account for a large portion of total charitable bequests. The most generous decedents' charitable bequest tax price (i.e., one minus the marginal tax rate) elasticity is not significantly greater than one in both our full sample and the subsample of the decedents filing federal estate tax returns. Our finding suggests that allowing charitable bequests to be deductible is not a treasury efficient policy for the most generous decedents. We also find that the tax price and wealth effects for the most generous decedents are overestimated by the Tobit model that has been traditionally utilized by prior studies. Furthermore, filers' charitable bequests are predicted to decrease if the estate tax is repealed.