A bivariate zero-inflated count data regression model with unrestricted correlation

This paper proposes a computationally simple bivariate zero-inflated count data regression model with an unrestricted correlation pattern. An application to data with excess of zeros on the demand for health services is given.     

On ridge estimators for the negative binomial regression model

The negative binomial (NB) regression model is very popular in applied research when analyzing count data. The commonly used maximum likelihood (ML) estimator is very sensitive to highly intercorrelated explanatory variables. Therefore, a NB ridge regression estimator (NBRR) is proposed as a robust option of estimating the parameters of the NB model in the presence of multicollinearity. To investigate the performance of the NBRR and the traditional ML approach the mean squared error (MSE) is calculated using Monte Carlo simulations. The simulated result indicated that some of the proposed NBRR methods should always be preferred to the ML method.     

The dependence structure between the Canadian stock market and the USD/CAD exchange rate: a copula approach

Abstract This paper investigates the dependence structure between the real Canadian stock returns and the real USD/CAD exchange rate returns, using the Symmetrized Joe‐Clayton (SJC) copula function. We estimate the SJC copula with monthly data over the period 1995:1 to 2006:12. Our results show significant asymmetric static and dynamic tail dependence between the real stock returns and the real exchange rate returns, such that the two returns are more dependent in the left than in the right tail of their joint distribution. We explain this asymmetric dependence in terms of an asymmetric interest rate policy by Canadian monetary authorities in response to changes in the real exchange rate during sub‐periods of falling and rising commodity prices.     

Kept back to get ahead? Kindergarten retention and academic performance

While most existing research concludes that grade retention generates no benefits for the retainees’ academic performance, holding low-achieving children back has been a popular practice for decades. Drawing on a recently collected nationally representative dataset in the US, this paper estimates the causal effect of repeating kindergarten on the retained children's academic performance. Since we observe children being held back only when they enroll in schools that permit kindergarten retention, this paper jointly models the choice of enrolling in a school that allows kindergarten retention, the decision of repeating kindergarten, and children's academic performance in higher grades. A control function approach is developed to estimate the resulting double-hurdle treatment model, which accounts for unobserved heterogeneity in the retention effect. A nearest-neighbor matching estimator is also implemented. Holding children back in kindergarten is found to have positive but diminishing effects on their academic performance up to third grade.     

Testing for bivariate stochastic dominance using inequality restrictions

We propose a test of bivariate stochastic dominance within a generalized framework for testing inequality restrictions, utilizing the covariance structure of the estimates of the joint distribution functions. Monte Carlo simulations and an empirical example assess its usefulness.     

Merger and acquisition FDI,relative wealth and relative access to bank credit: Evidence from a bivariate zero-inflated count model

We use a bivariate zero-inflated negative binomial model to examine Japanese merger and acquisition (M&A) FDI jointly with other types of Japanese FDI (or non-M&A FDI) into the United States. We find that for firms likely to engage in FDI, their rates of FDI are affected by the financial health of their main banks. However, only the rate of M&A FDI is affected by relative wealth. The rate of non-M&A FDI is affected by profitability and firm size. Our findings show the importance of distinguishing M&A FDI from non-M&A FDI and of considering the two types of FDI jointly.     

A generalized panel data switching regression model

This paper considers a generalized panel data model of polychotomous and/or sequential switching which can also accommodate the dependence between unobserved effects and covariates in the model. We showcase our model using an empirical illustration in which we estimate scope economies for the publicly owned electric utilities in the US during the period from 2001 to 2003.     

The choice of a foreign price measure in a Bayesian estimated new-Keynesian model for Israel

We estimate a small DSGE model by full information Bayesian techniques on the basis of Israeli data from 1995 to 2006. The model was first developed and estimated by means of classical GMM in Argov and Elkayam (2010), and since then it has been used at the Bank of Israel for monetary policy analysis. It is widely believed that in 2007 (out of sample year) as elsewhere worldwide, inflation rose in Israel due to high commodity prices in global markets. However, our baseline model attributes most of the high inflation in 2007 to supply shocks. One conjecture is that this model's result derives from the inappropriate original use of the unit value of imported consumer goods (which do not include unprocessed food and energy) as the main foreign price measure. We test this conjecture by re-estimating the model with various other foreign price measures that typically do reflect the global rise in commodity prices and compare the log-marginal likelihoods. We find that no other price measure outperforms the original choice in the sample period. Only the foreign trade-weighted CPI equals the performance of the original choice while improving the 2007 interpretation of inflation, and should therefore be considered the main foreign price measure. The proposed methodology for comparing the suitability of alternative measures for observable variables can be applied to any model with exogenous variables that are characterized by univariate equations.     

Testing for normality in linear regression models using regression and scale equivariant estimators

In this paper we provide a general solution to the problem of controlling the probability of a type I error in normality tests for the disturbances in linear regressions when using robust-regression residuals. We show that many classes of well-known robust regression estimators belong to the class of regression and scale equivariant estimators. It is these equivariance properties that are used to reduce the nuisance parameter space under the null, from which we develop Monte Carlo and Maximized Monte Carlo tests for the null of disturbance normality. Finally, we illustrate in a simulation experiment the potential power gains from using robust-regression residuals in testing this null hypothesis.     

An Alternative Core Inflation Measure

Abstract. We combine the ideas of the trimmed mean and the Edgeworth index to construct an alternative measure of core inflation named 'Trim of Most Volatile Components (TMVC)'. At each point of time, this measure trims away the components of the price index that have been most volatile in the recent past. Statistical tests indicate that neither the trimmed mean nor the Edgeworth index dominates the TMVC in terms of tracking trend inflation.     

Time and place where gold acts as an inflation hedge: An application of long-run and short-run threshold model

This study examines the short-run and long-run inflation hedging effectiveness of gold in the United States and Japan during the period of January 1971 to January 2010. Previous research has shown in the long-run that inflation tends to appropriately increase the price of gold in the U.S., leading to gold's popularity as an asset in portfolios to reduce the risk against sudden inflation. However, gold is only partially effective in hedging against inflation in Japan. This research found that the rigidity between the price of gold and the consumer price index affects the inflation hedging ability of gold in the long-run. The gold price is characterized by market disequilibrium induced by the price rigidity, causing the price of gold to be unable to response to changes in the CPI. To explore the inflation hedging ability of gold in the short-run, this study further examines the price rigidity in low and high momentum regime. It is found during the low momentum regimes that, gold return is unable to hedge against inflation in either the U.S. or Japan. However, during high momentum regimes, gold return is able to hedge against inflation in the U.S., while the price rigidity in Japan causes the price of gold to not fully hedge against inflation in the short-run.     

Dependence structure between nominal and index-linked bond returns: a bivariate copula and DCC-GARCH approach

This article investigates the dependence structure related to four French nominal and index-linked bonds with various maturities and reference indices. To achieve this aim, we estimate various copulas to select the appropriate one for our data. We also compare results obtained using the copula method with multivariate dynamic conditional correlation GARCH (DCC-GARCH) modelling. The major issue in this study is that the best copulas used to model the dependence among bond returns are the Plackett and Student models. We also find a dynamic correlation between bond returns. In particular, the relationship between nominal and indexed bonds is characterized by an asymmetric dependence. Moreover, the results obtained by the copula approach are confirmed by those obtained by multivariate GARCH modelling. Our empirical study provides a useful method that may be employed by decision-makers to quantitatively introduce dependence and spillover effects in their bond issuance policy. For investors, we propose optimal investment combinations in bonds with respect to their investment horizons.     

Measuring business cycles: A temporal disaggregation model with regime switching

In this paper, we propose a temporal disaggregation model with regime switches to disaggregate U.S. quarterly GDP into monthly figures. Alternative to the existing literature, our model is able to capture the nonlinear behaviors of both aggregated and disaggregated output series as well as the asymmetric nature of business cycle phases. To demonstrate the applicability of the proposed model, we apply the model with a Markov trend component to U.S. quarterly real GDP. The results suggest that the combination of a temporal disaggregation model with Markov switches leads to a successful representation of the data relative to the existing literature. Also, the inferred probabilities of unobserved states are clearly in close agreement with the NBER reference cycle on a monthly basis, which highlights the importance of nonlinearities in business cycle.     

The Tobit cointegrated vector autoregressive model: An application to the currency market

The Tobit cointegrated vector autoregressive model proposed in this study extends the existing methodology by allowing the censored variable to be nonstationary. The approach requires deriving the distribution of the cointegration rank test and simulating new critical values. The empirical application refers to the currency market. It has confirmed that the exchange rate is driven by four main forces: inflation, terms of trade, the perception of the country-specific risk, and the state of the currency market. Temporary disequilibria in the currency market arise not only from the “fundamental” factors, but also from the contagion effect.     

Estimates of a labour supply function using alternative measures of hours of work

Depending on data source, estimates of hours of work give widely different results both as to level and change. In this paper three alternative measures of hours worked are used to estimate a simple labour supply function to investigate if the estimated wage rate and income effects are data dependent as well. The measures used include those from time-use surveys and those from regular surveys. The latter are based on the responses to a question about normal weekly hours of market work. The results suggest that the estimates of the wage rate effects become much smaller when measures of normal hours are used compared to data collected for a well-defined time period close to the date of interview, such as time-use data. The income effects appear less sensitive to the choice of data.     

Steady state adjusting trends using a data-driven local polynomial regression

Economic variables usually follow a dynamic trend pattern. However, it is difficult to estimate this trend precisely as numerous economically- and statistically-based estimation methods exist. This contribution proposes a data-driven nonparametric trend that is local polynomial, to improve arbitrary trend estimations of commonly used methods concerning the selection of the smoothing parameter and the dependence structure. An iterative plug-in (IPI) algorithm determines the bandwidth endogenously and allows a theory-based interpretation of the length of growth processes. This length of the bandwidth reflects the lengths of the steady state periods. Consequently, the bandwidth identifies the time period of stable economic conditions and can detect economic changes. To demonstrate the power of this estimation approach, an extensive simulation study is performed. Furthermore, examples using US and UK GDP data along with a guide for the optimal choice of algorithms for empirical applications are provided. This proposed method yields new insights for growth dynamics, cyclical movements and their dependence.     

A structural dynamic microsimulation model of household savings and labour supply

A structural model of the household is described that represents current best-practice in the analysis of savings and labour supply responses to the policy environment. Care has been taken in specifying the model so that it represents an appropriate basis for the analysis of incentive effects to policy change, and for exploring the empirical support for alternative structural assumptions. Matching the model to survey data for the UK reveals some interesting puzzles in relation to the timing of retirement.     

Explaining the early years of the euro exchange rate: An episode of learning about a new central bank

Many observers were surprised by the depreciation of the euro after its launch in 1999. Handicapped by a short sample, explanations tended to appeal to anecdotes and lessons learned from the experiences of other currencies. Now sample sizes are just becoming large enough to permit reasonable empirical analyses. The model of this paper provides empirical support for the euro exchange rate to be affected by learning. By focusing on euro-area inflation as the key fundamental, the model is structured toward the dynamics of learning about ECB policy with regard to inflation. While a stated target inflation rate of 2 percent existed, it may be that market participants had to be convinced that the ECB would, indeed, generate low and stable inflation. With a prior distribution drawn from the pre-euro EMS experience and updating based upon the realized experience each month following the introduction of the euro, the evidence suggests that it was not until December of 1999 that the market assessed a greater than 50 percent probability that the inflation process had changed to a new regime. From this point on, trend depreciation of the euro ends and further increases in the probability of the new inflation process are associated with euro appreciation versus the US dollar, the British pound and the Japanese yen.     

Panel cointegration and the monetary exchange rate model

This paper re-examines the validity of the monetary exchange rate model during the post-Bretton Woods era for 18 OECD countries. Our analysis simultaneously considers the presence of both cross-sectional dependence and multiple structural breaks, which have not received much attention in previous studies of the monetary model. The empirical results indicate that the monetary model emerges only when the presence of structural breaks and cross-country dependence has been taken into account. Evidence is also provided suggesting that the breaks in the monetary model can be derived from the underlying purchasing power parity relation.     

A fractionally integrated exponential STAR model applied to the US real effective exchange rate

The aim of this paper is to study the dynamics of the US real effective exchange rate by capturing non-linearity and long-memory features. In this context, we use the family of fractionally integrated STAR (FISTAR) models proposed by van Dijk et al. (van Dijk, D., Franses, P.H., and Paap, R., 2002. A non-linear longmemory model with an application to US unemployment. Journal of Econometrics 110, 135–165.) in the case when the transition function is an exponential function and we develop an estimation procedure. Indeed, these models can take into account processes characterized by several distinct dynamic regimes and persistence phenomena.