The Role of Institutions in Cross-Section Income and Panel Data Growth Models: A Deeper Investigation on the Weakness and Proliferation of Instruments

This paper investigates the role of institutions in determining per capita income levels and growth. It contributes to the empirical literature by using different variables as proxies for institutions and by developing a deeper analysis of the issues arising from the use of weak and too many instruments in per capita income and growth regressions. The cross-section estimation suggests that institutions seem to matter, regardless if they are the only explanatory variable or are combined with geographical and integration variables, although most models suffer from the issue of weak instruments. The results from the growth models provides some interesting results: there is mixed evidence on the role of institutions and such evidence is more likely to be associated with law and order and investment profile; government spending is an important policy variable; collapsing the number of instruments results in fewer significant coefficients for institutions.

The Timing of Asset Trade and Optimal Policy in Dynamic Open Economies

Using a standard open economy DSGE model, it is shown that the timing of asset trade relative to policy decisions has a potentially important impact on the welfare evaluation of monetary policy at the individual country level. If asset trade in the initial period takes place before the announcement of policy, a national policymaker can choose a policy rule which reduces the work effort of households in the policymaker’s country in the knowledge that consumption is fully insured by optimally chosen international portfolio positions. But if asset trade takes place after the policy announcement, this insurance is absent and households in the policymaker’s country bear the full consumption consequences of the chosen policy rule. The welfare incentives faced by national policymakers are very different between the two cases. Numerical examples confirm that asset market timing has a significant impact on the optimal policy rule.

Negative investment in China: financing constraints and restructuring versus growth

This paper attempts to address a puzzle in China’s investment pattern: despite high aggregate investment and remarkable economic growth, negative net investment is commonly found at the microeconomic level. Using a large firm-level dataset, we test three hypotheses to explain the existence and extent of negative investment in each ownership group: what we term the efficiency (or restructuring) hypothesis, the (lack of) financing hypothesis, and the (slow) growth hypothesis. Our panel data probit estimations shows that negative investment by state-owned firms can be explained mainly by inefficiency: owing to over-investment or mis-investment in the past, these firms have had to restructure and to get rid of obsolete capital in the face of increasing competition and hardening budgets. The financing explanation holds for private firms, which have had to divest in order to raise capital. However, rapid economic growth weighs against both effects in all types of firms, with a larger impact for firms in the private and foreign sectors. A tobit model, estimated to examine the determinants of the amount of negative investment, yields similar conclusions.

Does China overinvest? Evidence from a panel of Chinese firms

This paper addresses the hotly-debated question: do Chinese firms overinvest? A firm-level dataset of 100,000 firms over the period of 2000-07 is employed for this purpose. We initially calculate measures of investment efficiency, which is typically negatively associated with overinvestment. Despite wide disparities across various ownership groups, industries and regions, we find that corporate investment in China has become increasingly efficient over time. However, based on direct measures of overinvestment that we subsequently calculate, we find evidence of overinvestment for all types of firms, even in the most efficient and most profitable private sector. We find that the free cash flow hypothesis provides a good explanation for China‟s overinvestment, especially for the private sector, while in the state sector, overinvestment is attributable to the poor screening and monitoring of enterprises by banks.

Forecasting Inflation Using Dynamic Model Averaging

We forecast quarterly US inflation based on the generalized Phillips curve using econometric methods which incorporate dynamic model averaging. These methods not only allow for coe¢ cients to change over time, but also allow for the entire forecasting model to change over time. We nd that dynamic model averaging leads to substantial forecasting improvements over simple benchmark regressions and more sophisticated approaches such as those using time varying coe¢ cient models. We also provide evidence on which sets of predictors are relevant for forecasting in each period.

Understanding Liquidity and Credit Risks in the Financial Crisis

This paper develops a structured dynamic factor model for the spreads between London Interbank Offered Rate (LIBOR) and overnight index swap (OIS) rates for a panel of banks. Our model involves latent factors which reflect liquidity and credit risk. Our empirical results show that surges in the short term LIBOR-OIS spreads during the 2007-2009 fi nancial crisis were largely driven by liquidity risk. However, credit risk played a more signifi cant role in the longer term (twelve-month) LIBOR-OIS spread. The liquidity risk factors are more volatile than the credit risk factor. Most of the familiar events in the financial crisis are linked more to movements in liquidity risk than credit risk.

A Nonlinear Panel Unit Root Test under Cross Section Dependence

We propose a nonlinear heterogeneous panel unit root test for testing the null hypothesis of unit-roots processes against the alternative that allows a proportion of units to be generated by globally stationary ESTAR processes and a remaining non-zero proportion to be generated by unit root processes. The proposed test is simple to implement and accommodates cross sectional dependence. We show that the distribution of the test statistic is free of nuisance parameters as (N, T) −! 1. Monte Carlo simulation shows that our test holds correct size and under the hypothesis that data are generated by globally stationary ESTAR processes has a better power than the recent test proposed in Pesaran [2007]. Various applications are provided.

Forecasting Inflation Using Dynamic Model Averaging

We forecast quarterly US inflation based on the generalized Phillips curve using econometric methods which incorporate dynamic model averaging. These methods not only allow for coe¢ cients to change over time, but also allow for the entire forecasting model to change over time. We nd that dynamic model averaging leads to substantial forecasting improvements over simple benchmark regressions and more sophisticated approaches such as those using time varying coe¢ cient models. We also provide evidence on which sets of predictors are relevant for forecasting in each period.

Alliance evolutions over the course of short-term dynamic psychotherapy: A case study

Background: Alliance evolutions, i.e. ruptures and resolutions over the course of psychotherapy, have been shown to be important descriptive features in different forms of psychotherapy, and in particular in psychodynamic psychotherapy. This case study of a client presenting elements of adjustment disorder undergoing short-term dynamic psychotherapy is drawn from a systematic naturalistic study and aims at illustrating, on a session-by-session-level, the processes of alliance ruptures and resolutions, by comparing both the client's and the therapist's perspectives. Method: Two episodes of alliance evolution were more fully studied, in relation to the evolution of transference, as well as the client's defensive functioning and core conflictual theme. These concepts were measured by means of valid, reliable observer-rater methods, based on session transcripts: the Defense Mechanisms Rating Scales (DMRS) for defensive functioning and the Core Conflictual Relationship Theme (CCRT) for the conflicts. Alliance was measured after each session using the Helping Alliance questionnaire (HAq-II). Results: The results indicated that these episodes of alliance rupture and resolutions may be understood as key moments of the whole therapeutic process reflecting the client's main relationship stakes. Illustrations are provided based on the client's in-session processes and related to the alliance development over the course of the entire therapy.

Corruption and Financial Intermediation in a Panel of Regions: Cross-Border Effects of Corruption

The importance of financial market reforms in combating corruption has been highlighted in the theoretical literature but has not been systemically tested empirically. In this study we provide a first pass at testing this relationship using both linear and nonmonotonic forms of the relationship between corruption and financial intermediation. Our study finds a negative and statistically significant impact of financial intermediation on corruption. Specifically, the results imply that a one standard deviation increase in financial intermediation is associated with a decrease in corruption of 0.20 points, or 16 percent of the standard deviation in the corruption index and this relationship is shown to be robust to a variety of specification changes, including: (i) different sets of control variables; (ii) different econometrics techniques; (iii) different sample sizes; (iv) alternative corruption indices; (v) removal of outliers; (vi) different sets of panels; and (vii) allowing for cross country interdependence, contagion effects, of corruption.

Co-movements in Real Effective Exchange Rates: Evidence from the Dynamic Hierarchical Factor Model

We analyze and quantify co-movements in real effective exchange rates while considering the regional location of countries. More specifically, using the dynamic hierarchical factor model (Moench et al. (2011)), we decompose exchange rate movements into several latent components; worldwide and two regional factors as well as country-specific elements. Then, we provide evidence that the worldwide common factor is closely related to monetary policies in large advanced countries while regional common factors tend to be captured by those in the rest of the countries in a region. However, a substantial proportion of the variation in the real exchange rates is reported to be country-specific; even in Europe country-specific movements exceed worldwide and regional common factors.

A Simple Characterization of Dynamic Completeness in Continuous Time

This paper investigates dynamic completeness of financial markets in which the underlying risk process is a multi-dimensional Brownian motion and the risky securities dividends geometric Brownian motions. A sufficient condition, that the instantaneous dispersion matrix of the relative dividends is non-degenerate, was established recently in the literature for single-commodity, pure-exchange economies with many heterogenous agents, under the assumption that the intermediate flows of all dividends, utilities, and endowments are analytic functions. For the current setting, a different mathematical argument in which analyticity is not needed shows that a slightly weaker condition suffices for general pricing kernels. That is, dynamic completeness obtains irrespectively of preferences, endowments, and other structural elements (such as whether or not the budget constraints include only pure exchange, whether or not the time horizon is finite with lump-sum dividends available on the terminal date, etc.)

Model Uncertainty in Panel Vector Autoregressive Models.

We develop methods for Bayesian model averaging (BMA) or selection (BMS) in Panel Vector Autoregressions (PVARs). Our approach allows us to select between or average over all possible combinations of restricted PVARs where the restrictions involve interdependencies between and heterogeneities across cross-sectional units. The resulting BMA framework can find a parsimonious PVAR specification, thus dealing with overparameterization concerns. We use these methods in an application involving the euro area sovereign debt crisis and show that our methods perform better than alternatives. Our findings contradict a simple view of the sovereign debt crisis which divides the euro zone into groups of core and peripheral countries and worries about financial contagion within the latter group.

Model Uncertainty in Panel Vector Autoregressive Models.

We develop methods for Bayesian model averaging (BMA) or selection (BMS) in Panel Vector Autoregressions (PVARs). Our approach allows us to select between or average over all possible combinations of restricted PVARs where the restrictions involve interdependencies between and heterogeneities across cross-sectional units. The resulting BMA framework can find a parsimonious PVAR specification, thus dealing with overparameterization concerns. We use these methods in an application involving the euro area sovereign debt crisis and show that our methods perform better than alternatives. Our findings contradict a simple view of the sovereign debt crisis which divides the euro zone into groups of core and peripheral countries and worries about financial contagion within the latter group.