开放经济下中国新凯恩斯混合菲利普斯曲线

本文采用广义矩方法估计开放经济下中国新凯恩斯混合菲利普斯曲线，结合中国现实选择工具变量。结果表明，使用混合成本作为通货膨胀的驱动因素在统计和经济意义上具有显著性，影响我国通货膨胀主要是资本成本与进口中间品成本；厂商定价行为既有前瞻性又有后顾性，但前瞻性处于主导地位，且价格具有较强的灵活性。     

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.     

Analyzing the effect of derivatives on the financial soundness of commercial banks in Italy: An approach based on the CAMELS framework

Italian economy is among the biggest economies in the Europe which suffered from the repercussions of the global financial crisis during this last decade. The weakness of Italian banking system coincides with the common debate about the implication of derivatives in the distress of banks’ soundness. Thus, the aim of our research is to examine the effect of derivative instruments on the banks’ soundness in Italy. To reach our goal, the CAMELS approach is employed to define the soundness of Italian commercial banks. To overcome the endogeneity issue of variables, an appropriate econometric procedure, namely the dynamic Generalized Method of Moments (GMM system) is applied using data from 22 commercial banks in Italy over the period 2005–2015. Explanatory variables are defined by derivative instruments (forwards, swaps, options, and futures), bank‐specific variable (bank's size as non‐CAMELS variable), industry‐specific variables (CR3, CR5, and HHI as indicators of bank's sector and market concentrations), and country‐specific variables (GDP and inflation). The main results reveal that the majority of the CAMELS indicators are favorably affected by derivative instruments especially forwards and options. The most important conclusion is that using derivative instruments does not threaten the financial soundness of commercial banks in Italy. As major implication decision‐makers and experts—after the global financial crisis—should not consider derivatives in part as responsible of the fragility of the Italian banking system.     

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.     

Credit risk,managerial behaviour and macroeconomic equilibrium within dual banking systems: Interest-free vs. interest-based banking industries

In this paper, an attempt has been made to explore the determinants of credit risk in the banking system with a particular interest toward the Islamic banking industry. We analyze the link between credit risk and a set of bank-specific and macroeconomic along with institutional variables using two complementary approaches. First, we investigate the factors of credit risk using one-step generalized method of moments (GMM) system estimator. Then, we explore the feedback between credit risk and its determinants in a panel vector autoregressive (PVAR) model. We have used a sample of Middle Eastern, North African (MENA) and Asian countries to apply our model. The major purpose of this paper is to find factors that could explain credit risk within the interest-free banking system relative to the interest-based one.     

信息化对制造业升级的影响机制研究

信息化对制造业升级的影响日益深远，但其影响机制也更加复杂。通过微观、宏观双视角定性论述，借助GMM模型对中国283个城市2004-2014年的面板数据进行定量测度，探讨了信息化对制造业升级的影响机制。结果显示：信息化与制造业升级存在倒U型关系，当信息化程度未跨过风险拐点时，其对制造业升级会产生促进作用；信息化程度跨过风险拐点后，信息化对制造业升级的促进作用呈下降趋势。研究表明信息化并不总是促进制造业升级，信息化是机遇也是挑战，各地区需要因地制宜，结合自身工业化水平来发展信息化。     

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.     

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.