Convenient estimators for the panel probit model: Further results

Bertschek and Lechner (1998) propose several variants of a GMM estimator based on the period specific regression functions for the panel probit model. The analysis is motivated by the complexity of maximum likelihood estimation and the possibly excessive amount of time involved in maximum simulated likelihood estimation. But, for applications of the size considered in their study, full likelihood estimation is actually straightforward, and resort to GMM estimation for convenience is unnecessary. In this note, we reconsider maximum likelihood based estimation of their panel probit model then examine some extensions which can exploit the heterogeneity contained in their panel data set. Empirical results are obtained using the data set employed in the earlier study. Helpful comments and suggestions by Irene Bertschek and Michael Lechner are gratefully acknowledged. This paper has also benefited from comments by two anonymous referees and from seminar participants at the Center for Health Economics at the University of York. Any remaining errors are the responsibility of the author.     

Estimation methods for stochastic volatility models: a survey

Abstract.  Although stochastic volatility (SV) models have an intuitive appeal, their empirical application has been limited mainly due to difficulties involved in their estimation. The main problem is that the likelihood function is hard to evaluate. However, recently, several new estimation methods have been introduced and the literature on SV models has grown substantially. In this article, we review this literature. We describe the main estimators of the parameters and the underlying volatilities focusing on their advantages and limitations both from the theoretical and empirical point of view. We complete the survey with an application of the most important procedures to the S&P 500 stock price index.     

Monetary and Fiscal Policy Interactions in the Euro Area

The problem of monetary and fiscal policy interactions is an important issue for the euro area, since the individual member states of the EMU are responsible for their fiscal policies but monetary policy is pursued by a single monetary authority, the ECB. This paper is concerned with empirical evidence on monetary and fiscal policy interactions in the euro area. We first explore fiscal regimes with a VAR model and find empirical evidence that a non-Ricardian fiscal policy has been pursued in both France and Germany. As an example, we then study how one member state of the EMU, namely, Italy, is responding to the common monetary policy with its fiscal policy and find that Italian fiscal policy seemed to be counteractive to the common monetary policy between 1979 and 1998. In order to study monetary and fiscal policy interactions in a more general way, we explore time-varying interactions by estimating a State-Space model with Markov-switching for some Euro-area countries. There appear to be some regime changes in monetary and fiscal policy interactions in France and Germany, but the interactions between the two policies are not strong. Moreover, the two policies have not been accommodative but counteractive to each other. Finally we explore forward-looking behavior in policy interactions and find that expectations do not seem to have played an important role in the policy designs.     

Financial Sector Risk and the Stock Returns: Evidence from Tokyo Stock Exchange Firms

We investigate whether the activity of financial firms creates value and/or risk to the economy within the asset pricing framework. We use stock return data from nonfinancial firms listed in the first section of the Tokyo Stock Exchange. The value-weighted index that is solely composed of nonfinancial firms is augmented with the index of the firms from the financial sector, and we estimate multivariate asset pricing model with these two indices. We note that our procedure can simultaneously take into account the cross-holding phenomena among Japanese firms, especially between the financial sector and the nonfinancial sector. Our augmented index model performs well both with cross-sectional Fama and MacBeth regression test and GMM test. Our two index model with additional Fama and French's HML factor can capture cross-sectional variations of the returns of sample portfolios better than the original Fama and French model can, when measured by Hansen and Jagannathan distance measure. We find that this additional new sector variable can be a substitute for Fama and French's size factor, but not related to the bond index return. This variable has similar factor characteristic as money supply growth or the term structure, but the latter variables contain more information than the former. Morever, our financial sector model helps explain the return and risk structure of Japanese firms during the so-called bubble period.     

Is ex-post credit risk affected by the cycles? The case of Italian banks

The objective of this research is to empirically examine if both credit and business cycle affect the ex-post credit risk (i.e. non-performing loans) in the banking system of Italy for the period 1995Q1–2014Q1. The increase in NPLs post-2008 has put into question the robustness of many European banks and the stability of the whole sector. It still remains a serious challenge, especially in Italy which is one of the countries that hit by the financial crisis. By employing fixed and random effects and a dynamic GMM estimation as econometric methodologies I find results that underline common causes for NPLs. Higher NPLs in Italy are mostly due to worse macroeconomic conditions (i.e. bad phase of business cycle) and due to excess credit. Through a Granger causality test, my arguments found even more support. Such findings can be helpful when designing macro-prudential as well as NPL resolution policies.     

Risk-Taking Behavior and Capital Adequacy in a Mixed Banking System: New Evidence from Malaysia Using Dynamic OLS and Two-Step Dynamic System GMM Estimators

This study is the first attempt to investigate the relationship between the level of risky assets and capital level in a mixed Malaysian banking system covering 83 months starting December 2006. The results of dynamic ordinary least squares indicate positive relationship between capital ratio (CAR) and risk-weighted asset ratio (RWA) in the long run. Furthermore, the causality analysis based on panel vector error correction model (VECM) and two-step dynamic system generalized method of moments indicates unidirectional causality from CAR to RWA. Our results further suggest that higher capital growth and capital buffer provide an extra cushion for the Malaysian banks to pursue relatively riskier financial activities, and the nature of risk-taking behavior of Islamic banks follows that of the conventional banks.     

Measuring the liquidity part of volume

Based on the concept that the presence of liquidity frictions can increase the daily traded volume, we develop an extended version of the mixture of distribution hypothesis model (MDH) along the lines of Tauchen and Pitts (1983) to measure the liquidity portion of volume. Our approach relies on a structural definition of liquidity frictions arising from the theoretical framework of Grossman and Miller (1988), which explains how liquidity shocks affect the way in which information is incorporated into daily trading characteristics. In addition, we propose an econometric setup exploiting the volatility–volume relationship to filter the liquidity portion of volume and infer the presence of liquidity frictions using daily data. Finally, based on FTSE 100 stocks, we show that the extended MDH model proposed here outperforms that of Andersen (1996) and that the liquidity frictions are priced in the cross-section of stock returns.     

亚洲新兴经济体国际资本流动驱动因素研究——基于GMM模型的实证分析

理解资本流入的驱动因素,对于设计一个有效的资本流动管理政策框架至关重要。本文研究了1998年至2018年间45个新兴经济体面临的各类资本流动的驱动因素,重点分析了资本流向亚洲地区的驱动因素与其他地区的共性和异质性。使用广义矩估计方法(GMM)对面板数据集的实证结果表明,对新兴经济体而言,制度质量和国内因素对吸引资本流入具有重要影响;对亚洲地区来说,人均收入增长和贸易开放是吸引资本流入的重要驱动因素,国内外利差水平和实际有效汇率变动对吸引组合投资和其他投资具有显著影响,VIX指数和影子利率对亚洲新兴经济体资本流动规模的影响也具有重要影响。这表明,在设计管理资本流入的政策框架时,全球经济金融合作和政策协调应被考虑在内。     

地方政府财政支农支出与农村居民消费——来自中国29个省市面板数据的经验证据

本文在消费者最优消费路径选择的基本框架下,构建了一个政府财政支农与农村居民消费的动态最优化模型,理论分析表明:地方政府财政支农支出的增加,对于农村居民消费水平的提高具有促进作用。基于1995-2008年的省际面板数据,采用工具变量GMM方法对该结论进行的实证检验发现:在通过多工具变量克服变量内生性之后,地方政府财政支农支出对农村居民消费具有显著的促进作用,地方政府财政支农支出每增加1%,我国农村居民消费将增加0.1367%;进一步的因素分解显示,地方政府财政支农支出对农村居民消费的平均贡献度为8.72%,且有逐年增大的趋势。此外,财政支农支出对农村居民消费的影响存在区域差异性,即财政支农支出对我国中西部地区农村居民消费的影响程度大于东部地区。     

The house price determination process: Rational expectations with a spatial context

Applying the rational expectations hypothesis, this essay models the current value of a house as the conditional expectation of the discounted stream of housing services accruing to the owner of the house. The value of housing services is determined by neighborhood effects as well as the physical attributes of the property itself. In the existing hedonic literature, future transactions have not been utilized to describe neighborhood effects. The rational expectations asset pricing model in this study accounts for expected future neighborhood effects as well as observed current neighborhood effects. The reduced form of the rational expectations model is a spatial autoregressive (SAR) model with two spatial lags. After employing the generalized method of moments (GMM) in estimating the spatial asset pricing model, I find that both expected future transactions and prior transactions in the neighborhood are significant. The inclusion of expected future transaction prices in the neighborhood takes into account the influence of expected changes in the community and factors these potential changes into the current house price. This is consistent with forward-looking households. The forward-looking model generates superior out-of-sample prediction performance relative to both the conventional hedonic model without considering neighborhood effects or the standard spatial hedonic model including only past transactions.