THE CIRCULAR RELATIONSHIP BETWEEN INEQUALITY,LEVERAGE, AND FINANCIAL CRISES

In this paper, we put into perspective the recent literature which points to inequality as a possible cause of credit bubbles, by reintegrating it into a more general analysis on the two-way relationship between inequality and finance. We focus more specifically on situations where high inequalities and widespread access to credit coexist, and argue that, even when institutions maintain more or less equal access to finance, there may be a dynamic, positive circular relationship between inequality and financial development. However, even if there is some evidence in the literature of a positive causal impact of inequality on credit, this does not preclude other important, cofounding factors. The conclusions concerning the distributional impact of finance are more ambiguous. A survey of the empirical literature highlights several issues that must be tackled. First, endogeneity: reverse causality and coincidental factors are major concerns. Second, the choice of consistent measurements for the key variables (both credit and inequality) has strong empirical implications, and must be grounded on relevant theoretical channels. Third, those circular dynamics have substantial policy implications for emerging economies, since an increasing number face a joint increase in inequality and credit.     

MODEL UNCERTAINTY AND SCENARIO AGGREGATION

This paper provides a coherent method for scenario aggregation addressing model uncertainty. It is based on divergence minimization from a reference probability measure subject to scenario constraints. An example from regulatory practice motivates the definition of five fundamental criteria that serve as a basis for our method. Standard risk measures, such as value‐at‐risk and expected shortfall, are shown to be robust with respect to minimum divergence scenario aggregation. Various examples illustrate the tractability of our method.     

Does easy availability of cash affect corruption? Evidence from a panel of countries

Using annual panel data of 54 countries for the period 2005-14, we examine whether currency in circulation, both aggregate and in large denominations, affects the level of corruption in a country. Standard panel data models suggest that the ratios of (i) aggregate currency in circulation to M1 and, (ii) large denomination banknotes to M1 are both statistically significant determinants of corruption. Tests for reverse causality within a panel Granger framework reveal a uni-directional causality of corruption with the first variable, but a bi-directional one with the second. These findings suggest that a limitation in the supply of high-denomination banknotes, inter alia, could be a tool to fight corruption, and bring to the fore the important role of payment systems, extending an earlier study by Goel and Mehrotra (2012). The results also highlight that, along with the government, the central bank of an economy can also play an important role in the fight against corruption.     

中国服务贸易与货物贸易因果关系分析——基于误差修正模型的中美对比分析

运用时间序列分析和因果关系分析,对比分析中美两国各自货物贸易和服务贸易之间的延迟引导关系。协整分析和格兰杰因果关系检验结果明确了中国实现服务贸易与货物贸易可持续发展的内生性难题:中国服务出口的增长最终促进同时期货物出口的增长,与美国服务出口的增长最终促进同时期服务出口的增长这一内在动力差别较大。     

Projecting county pulpwood production with historical production and macro-economic variables

We explored forecasting of county roundwood pulpwood production with county-vector autoregressive (CVAR) and spatial panel vector autoregressive (SPVAR) methods. The analysis used timber products output data for the state of Florida, together with a set of macro-economic variables. Overall, we found the SPVAR specification produced forecasts with lower error rates compared to CVAR specifications. Nonetheless, high forecast errors across counties revealed the uncertainty associated with projecting volumes of county pulpwood production.     

Stock volatility and pension funds under an individual capitalization-based system

The existence of feedback effects between volatility and institutional investor holdings has been extensively studied for the United States. This article contributes to the literature by investigating this issue for Pension Fund Administrators (PFAs) in Chile. To this end, data on PFAs' holdings is gathered for 42 firms actively traded on the Santiago Stock Exchange during December 2002–July 2008. The main findings of this study are the following. First, an increase in PFAs' stock holdings translates into a mild effect on stock return volatility. Second, an increase in stock return volatility leads to a moderate decrease in PFAs' stock holdings, suggesting PFAs' preference for safer stocks. The key policy implication of these conclusions is that PFAs' stock trading does not have a destabilizing impact on the domestic stock market.     

Is devaluation expansionary or contractionary: Evidence based on vector autoregression with sign restrictions

The purpose of the paper is to examine the impact of real exchange rate changes – real devaluation or real depreciation – on outputs in 16 countries that fall within one of the three groups: Latin American countries, Asian countries, and non-G3 developed countries. For the first time in the contractionary devaluation literature, the analysis is based on a Vector Autoregression (VAR) model with sign restrictions method by Uhlig (2005) and Fry and Pagan (2011). The exchange rate shock is identified by imposing restrictions on the signs of impulse responses for a small subset of variables. The findings are as follows: (1) whether output increases after a real devaluation or not has little to do with whether the current account improves or not; (2) Latin American countries are quite homogenous in that the current account generally improves while output decreases after real devaluation; and (3) contractionary devaluation could happen in developed countries as well as in developing countries.     

陕西省人力资本水平与产业结构关系研究

陕西省的经济发展在全国处于一般水平,与其人力资本水平不甚匹配,引起这一现状的原因到底是什么?通过人力资本结构对人力资本水平进行划分,得出陕西省专业人力资本与产业结构升级高度相关,但是创新是产业结构高度化的动力和基础,因此陕西省的人力资本结构应当以扩大企业家人才的比例为目标进行调整,以促进产业机构升级,进而促进陕西省经济发展水平。     

Bias correcting adjustment coefficients in a cointegrated VAR with known cointegrating vectors

The maximum likelihood estimator of the adjustment coefficient in a cointegrated vector autoregressive model (CVAR) is generally biased. For the case where the cointegrating vector is known in a first-order CVAR with no intercept, we derive a condition for the unbiasedness of the maximum likelihood estimator of the adjustment coefficients, and provide a simple characterization of the bias in case this condition is violated. A feasible bias correction method is shown to virtually eliminate the bias over a large part of the parameter space.     

Investor Sentiment Influence on the Risk-Reward Relation in the Taiwan Stock Market

We examine the influence of investor sentiment on the risk-reward relationship in the Taiwan stock market. Regression results show that the risk-reward relationship is weakly positive (significantly negative) under low (high) levels of investor sentiment. Granger causality tests indicate unidirectional, not bidirectional, causal relationships. Moreover, the negative return-variance relationship is more strongly characteristic of the over-the-counter index than of the Taiwan Stock Exchange weighted index, indicating that an unreasonable risk-reward trade-off may be more prevalent in emerging markets than in mature markets. Finally, the Wald test demonstrates that industry effects on the risk-reward relationship may be negligible.