A network based fintech inclusion platform

The paper evaluates, from a sustainable finance viewpoint, a machine learning model implemented in a fintech platform, whose aim is to assign credit ratings. The aim of the model is to learn from both micro economic data and macro economic trends the credit rating of companies that ask for credit. We show that the proposed model is able to reward the companies that have better financial performances with better ratings and, therefore, a higher probability/lower cost of obtaining credit. At the same time, the model correctly takes into account the overall evolution of the economy, favoring financial inclusion for the more penalized economic sectors, particularly during crisis times. The model, its application to credit rating, and its evaluation, are illustrated with reference to more than 100,000 European companies before and during the COVID-19 pandemic crisis. The results shows that, while the impact of the financial variables does not change over time, and particularly during the pandemic, the impact of sectors changes considerably, favoring financial inclusion and resilience.     

Comparing probabilistic forecasts of the daily minimum and maximum temperature

Understanding changes in the frequency, severity, and seasonality of daily temperature extremes is important for public policy decisions regarding heat waves and cold snaps. A heat wave is sometimes defined in terms of both the daily minimum and maximum temperature, which necessitates the generation of forecasts of their joint distribution. In this paper, we develop time series models with the aim of providing insight and producing forecasts of the joint distribution that can challenge the accuracy of forecasts based on ensemble predictions from a numerical weather prediction model. We use ensemble model output statistics to recalibrate the raw ensemble predictions for the marginal distributions, with ensemble copula coupling used to capture the dependency between the marginal distributions. In terms of time series modelling, we consider a bivariate VARMA-MGARCH model. We use daily Spanish data recorded over a 65-year period, and find that, for the 5-year out-of-sample period, the recalibrated ensemble predictions outperform the time series models in terms of forecast accuracy.     

Regional integration: an empirical assessment of Russia

Using a statistical model of commodity trade, we quantify the evolution of regional economic integration within Russia during 1995–1999, and explore potential determinants of this evolution. Our integration measure exhibits rich regional variation that, when aggregated to the national level, fluctuates substantially over time. In accounting for this behavior, we draw in part on theoretical models that emphasize the potential role of openness to international trade and regional disparities in income in threatening economic integration. Controlling for a host of additional regional- and national-level variables, we find a strong negative correspondence between openness to international trade and internal economic integration.     

Evolution in a General Equilibrium framework

In this paper, we consider a general equilibrium model in which the economies are characterized by the distribution of firms on a set of branches of production; we will show that based on the decisions of the managers of the firms, it is possible to build a dynamic system whose solutions reproduce the possible trajectories of the economy. Once the initial state of an economy is known, that is, the initial distribution of firms, we will have a unique solution for this dynamic system, which will coincide with the evolution of the economy, that is, the evolution of prices and equilibrium allocations.The investment decisions of the administrators of the companies will change the distribution over the set of existing productive branches, which in turn will produce changes in the wealth of consumers who are also shareholders of the companies and then as a consequence, their demand will change, and therefore the equilibrium allocations and prices will too.In most cases, these decisions lead to an improvement in the efficiency of the productive side of the economy and an increase in the welfare of the economy as a whole, but, as we will show, under some particular circumstances, even when it comes to rational decisions from the point of view of administrators, this can lead to undesirable repercussions on the welfare of consumers. Besides, in a neighborhood of a critical economy, even when these decisions may involve small changes in the distribution of companies, they can cause abrupt and unexpected changes in the behavior of the economy, or in other words, they can cause an economic crisis. These are characterized by large changes in the prices, in the demand, and in the supply of goods. In contrast, in a sufficiently small neighborhood of a regular economy, small changes in the distribution of firms produced by the investment decisions of managers do not lead to large changes in the subsequent behavior of the economy. We will exemplify these statements with several numerical examples.     

Testing the convergence hypothesis: a longitudinal and cross-sectional analysis of the world trade web through social network and statistical analyses

Different theoretical perspectives support opposite views on convergence: although the dominant view is that convergence is the inevitable outcome of globalization, divergentists (that is, world-system economists and, potentially, also evolutionary geographic ones) argue that convergence forces could be annihilated by the need to keep power relationships within the international division of labor. Even when limiting the convergence issue to international trade, the debate has so far been inconclusive, because various studies have dealt with different and/or short time series or selected too small and different sets of countries. Moreover, none of these studies have analyzed trade patterns and have instead been limited to the aggregate value. Here, through a social network analysis, we examine the world trade patterns from 1980 to 2016 (1980–1992, 1993–2007 and 2008–2016) of at least 164 countries, which have been divided into import and export patterns and into four groups of countries: from core countries to far periphery ones. We test the convergence hypothesis in two directions: the level and trend of convergence, and its possible determination by means of structural or economic globalization, measured in terms of exchanges density and economic values, respectively. We have found that the convergence hypothesis only seems to be confirmed when considering the pure structural aspect and core countries. Conversely, economic convergence—which also includes the structural dimension—has been found to be high for core countries and to increase over time. Moreover, our analysis shows that economic globalization influences convergence, albeit in a strongly negative way. Therefore, our findings seem to support divergentists and the convergence hypothesis should be rejected.

     

Diagnostic Tests of Cross‐section Independence for Limited Dependent Variable Panel Data Models*

This article considers the problem of testing for cross‐section independence in limited dependent variable panel data models. It derives a Lagrangian multiplier (LM) test and shows that in terms of generalized residuals of Gourieroux et al. (1987) it reduces to the LM test of Breusch and Pagan (1980) . Because of the tendency of the LM test to over‐reject in panels with large N (cross‐section dimension), we also consider the application of the cross‐section dependence test (CD) proposed by Pesaran (2004) . In Monte Carlo experiments it emerges that for most combinations of N and T the CD test is correctly sized, whereas the validity of the LM test requires T (time series dimension) to be quite large relative to N. We illustrate the cross‐sectional independence tests with an application to a probit panel data model of roll‐call votes in the US Congress and find that the votes display a significant degree of cross‐section dependence.     

Multivariate partial adjustment of financial ratios: a Bayesian hierarchical approach

In this paper we propose a multivariate extension of the partial adjustment model of financial ratios. To that end, we use a dynamic factor model which assumes that financial ratios measuring, essentially, the same economic–financial dimension of the firm evolve in a similar way, reflecting the evolution of the common factor. The proposed model is hierarchical with three levels. The first describes the relationship between each ratio and its common factor; the second describes the evolution of the common factors over time by means of Lev's ( 1969 ) partial adjustment model; and the third analyzes the similarity of firms' adjustment coefficients, taking into account their characteristics. The methodology is applied to the analysis of a set of financial ratios related to the business and financial structure of the firm. Copyright © 2008 John Wiley & Sons, Ltd.     

我国城乡居民收入差距的数理经济模型及其实证研究

深化收入分配制度改革,增加城乡居民收入是我国改革的根本目标。改革开放以来,我国的经济持续快速发展,人民的生活水平得到了很大提高,但与此同时,我国也出现了严重的居民收入差距。文章在对收入分配的影响因素进行分析的基础上,建立一个回归模型分析所有制结构的演变与居民收入的关系,进而通过协整分析和格兰杰因果检验,对二元经济结构与城乡居民收入差距之间的数量关系进行了分析和检验。研究结论表明:转型期所有制结构的演变以及二元经济结构是我国居民收入差距呈扩大趋势的根本原因,二元经济结构与城乡居民收入差距具有单向的格兰杰原因。最后针对城乡收入差距扩大的趋势提出相应的解决对策。     

Nowcasting growth using Google Trends data: A Bayesian Structural Time Series model

This paper investigates the benefits of internet search data in the form of Google Trends for nowcasting real U.S. GDP growth in real time through the lens of mixed frequency Bayesian Structural Time Series (BSTS) models. We augment and enhance both model and methodology to make these better amenable to nowcasting with large number of potential covariates. Specifically, we allow shrinking state variances towards zero to avoid overfitting, extend the SSVS (spike and slab variable selection) prior to the more flexible normal-inverse-gamma prior which stays agnostic about the underlying model size, as well as adapt the horseshoe prior to the BSTS. The application to nowcasting GDP growth as well as a simulation study demonstrate that the horseshoe prior BSTS improves markedly upon the SSVS and the original BSTS model with the largest gains in dense data-generating-processes. Our application also shows that a large dimensional set of search terms is able to improve nowcasts early in a specific quarter before other macroeconomic data become available. Search terms with high inclusion probability have good economic interpretation, reflecting leading signals of economic anxiety and wealth effects.     

Structural change and female participation in recent economic growth: a multisectoral analysis for the Spanish economy

ABSTRACT

Economic growth has different impacts on gender gaps. In recent decades the growing participation of women in the labour market has reduced the gender employment gap, however a notable gender pay gap still persists standing at around 15% on average in the European Union. In this context, this paper evaluates the impact of economic growth patterns on the evolution of gender employment and pay gaps. First, sectorial feminization, direct discrimination, and structural change factors are identified and evaluated as ways to explain changes observed in the gender pay gap. Second, we explore the influence of demand, technology, and intensity factors on the evolution of employment combining gender, skill, sectorial, and temporal perspectives. As a case study, we examine Spanish economic growth from 1980 to 2007 and the influences on the size, composition (by skill), and distribution (by sector) of female and male employment, as well as the consequences for gender gaps. Our results show that structural change contributed to reduce the gender employment gap in Spain; while the evolution of the gender pay gap is less conclusive, following a sort of inverted U-shape. This paper shows the suitability and potential of the multisectorial input–output framework to analyse structural and technological changes and their impacts on the gender employment and pay gaps.     

The economics of retail firms

This paper identifies retail firms as an economic institution which delivers explicit products or services to consumer together with a variety of distribution services that determine the levels of distribution costs experienced by consumers in their purchase activities. The demand for the retailer's product is derived from a household production model in which the levels of distribution services provided by the retailer play the role of fixed inputs in the household's production functions. The supply of the retailer's product is derived from a joint cost function which is non-decreasing in the levels of distribution services provided. Profit-maximizing behavior in monopolistically competive markets shows that retail firms have special economic incentives to become complex organizations by integrating backwards, offering multiple explicit products and operating in more than one market. In addition, monopolistically competitive retail firms in long-run equilibrium will exhibit excess capacity, price dispersion and product choice in distribution services.     

Modelling the spatiotemporal distribution of the incidence of resident foreign population

Many European countries have recently experienced a substantial increase in the proportion of immigrants in their populations. The incidence of resident foreigners calculated at a national level does not provide information on the local spatial and temporal distribution of the phenomenon. This information may be of crucial importance for planning local policies. In this article, we suggest a tool for practitioners to provide spatiotemporal maps representing the local distribution of the incidence of resident foreigners in the territory, and changes in spatial trends over time. We illustrate this with Italian data at a municipal level, for the period 2003–2008. To account for spatiotemporal interactions in the data, we propose using a generalized additive model incorporating a smoother of the time and space dimensions. Specifically, we set up a tensor product smoother combining a cubic regression spline basis for time and a soap film spline basis for space. This approach provides a consistent framework to produce spatiotemporal maps which could be effectively used by policy makers to decide the allocation of economic resources at a local level.     

Bayesian treatment of the independent student-t linear model

This article takes up methods for Bayesian inference in a linear model in which the disturbances are independent and have identical Student-t distributions. It exploits the equivalence of the Student-t distribution and an appropriate scale mixture of normals, and uses a Gibbs sampler to perform the computations. The new method is applied to some well-known macroeconomic time series. It is found that posterior odds ratios favour the independent Student-t linear model over the normal linear model, and that the posterior odds ratio in favour of difference stationarity over trend stationarity is often substantially less in the favoured Student-t models.     

Estimating the returns to schooling: a likelihood approach based on normal mixtures

In this paper we develop likelihood‐based methods for statistical inference in a joint system of equations for the choice of length of schooling and earnings. The model for schooling choice is assumed to be an ordered probit model, whereas the earnings equation contains variables that are flexible transformations of schooling and experience, with corresponding coefficients that are allowed to be heterogeneous across individuals. Under the assumption that the distribution of the random terms of the model can be expressed as a finite mixture of multinormal distributions, we show that the joint probability distribution for schooling and earnings can be expressed on closed form. In an application of our method on Norwegian data, we find that the mixed Gaussian model offers a substantial improvement in fit to the (heavy‐tailed) empirical distribution of log‐earnings compared to a multinormal benchmark model. Copyright © 2010 John Wiley & Sons, Ltd.     

A new class of inverse Gaussian type distributions

The elliptical laws are a class of symmetrical probability models that include both lighter and heavier tailed distributions. These models may adapt well to the data, even when outliers exist and have other good theoretical properties and application perspectives. In this article, we present a new class of models, which is generated from symmetrical distributions in and generalize the well known inverse Gaussian distribution. Specifically, the density, distribution function, properties, transformations and moments of this new model are obtained. Also, a graphical analysis of the density is provided. Furthermore, we estimate parameters, propose asymptotic inference and discuss influence diagnostics by using likelihood methods for the new distribution. In particular, we show that the maximum likelihood estimates parameters of the new model under the t kernel are down-weighted for the outliers. Thus, smaller weights are attributed to outlying observations, which produce robust parameter estimates. Finally, an illustrative example with real data shows that the new distribution fits better to the data than some other well known probabilistic models.     

Preserving a Professional Institution: Emotion in Discursive Institutional Work

We studied the discursive institutional work written by pharmacy leaders as part of a larger institutional project to preserve the institution of pharmacy. Our analysis of monthly editorials printed in the Journal of the American Pharmacists Association from 1960 to 2003 shows how different discrete emotions were systematically incorporated in specific rhetorical argument structures over the course of an institutional project. In contrast to previous research, we show how discursive institutional work that is directed to members of the same specific social group (e.g., a profession) can vary over time in response to significant events and changes in practices of the target audience. Our longitudinal study shows that the relative frequency of argument types, the incorporation of emotion, and the content of rhetorical argumentation changed over time. We contribute to theory about the role of emotions in discursive institutional work by unpacking the role of discrete emotions and showing how such discourse evolves over time in concert with field conditions.     

THE DEVELOPMENT OF REGIONAL INTEGRATION IN EAST ASIA: FROM THE VIEWPOINT OF SPATIAL ECONOMICS

This paper examines the recent evolution of regional integration in East Asia, and discusses the prospects and tasks of further integration. After an overview of the globalization and regional integration trend in EU, NAFTA and East Asia during the past half-century, we introduce the basic framework of spatial economics, often called the new economic geography. In terms of globalization and regional integration, it is important to examine the general effects of decreasing transport costs (broadly defined) on spatial distribution of economic activities. Given this theoretical framework, we examine the changing economic interdependency within East Asia, as well as that between East Asia and the rest of the world over the last three decades. Next, we focus on regional diversity and disparity in East Asia. Finally, we compare the regional integration in EU with that of East Asia, and examine the tasks and prospects of further promotion of East Asian integration.     

FDI与出口贸易结构关系研究(1978～2005年)——基于DLM与TVP模型的检验

本文分析初级产品、工业制品出口贸易结构及出口贸易方式结构变化,并研究其变化原因,同时借助分布滞后模型及变参数经济计量模型,探讨1978年以来FDI对出口贸易结构变化的影响。研究认为出口贸易存在巨大利润空间与政策空间,并促成外资流入规模逐年扩大;但伴随着外资的流入,出口贸易结构并未优化,需要通过政策措施调整FDI的流入规模与方向,进一步实现贸易结构升级。