Exchange rates dynamics revisited: a panel data test of the fractional integration order

We test the possibility that exchange rates from nine developed countries have a unit root against the alternate possibility that they are fractionally integrated. Theoretically, exchange rates are only expected to follow a random walk under restrictive assumptions. However, most traditional unit root tests cannot reject a unit root in exchange rates, and time series tests that allow for fractional integration have given inconclusive results. To increase the power of the test of the integration order we develop two panel data tests of the fractional integration order. Monte Carlo simulations show that these tests are correctly sized and have relatively high power compared to other similar tests. Moreover, our empirical results show that we can reject a unit root in exchange rates with a high probability, but the integration order is close to one. This indicates that exchange rates are mean-reverting, although the reversion is slow, resulting in long swings.     

GMM estimation of panel data models with time-varying slope coefficients

A difference/system generalized method of moments (GMM) model that imposes time-constant coefficients is common in empirical studies using panel data. However, a rejection by the Sargan–Hansen test is sometimes a serious concern for researchers. We highlight the fact that the Sargan–Hansen test for GMM estimators applied to panel data is a joint test of valid orthogonality conditions and coefficient stability over time. A possible reason for a rejection is therefore that the slope coefficients vary over time. One solution is to estimate an empirical model in which the coefficients are time specific. We apply this solution to the system GMM estimator of simple nondynamic Cobb–Douglas production functions for a selection of Swedish industries and find that relaxing the assumption of constant slope coefficients results in more satisfactory outcomes of the Sargan–Hansen test.     

Using real-time electricity data to estimate response to time-of-use and flat rates: an application to emissions

Using a generalized McFadden specification, we estimate the determinants of hourly response for the years 2006 through 2010 for all 16 standard retail customers who were on an optional real-time electricity rate offered by Duke Energy as of 2010, and provide a method to estimate how these customers would respond to time-of-use (TOU) and flat rates. We generalize the model to allow for inter-day response, as well as threshold prices, above which individual customer response may increase or decrease. With these inclusions, we find hourly elasticity for the group of customers to be as large as ?0.7, larger than previous studies. We apply the method to examine a recent finding that time-differentiated rates could increase electric utility emissions. However, that result did not differentiate between real-time and TOU rates, and furthermore held energy use constant in comparing flat rates and time-differentiated rates. We perform a case study to examine emissions of SO₂, NOx, Hg, and CO₂ based on predicted energy use changes as well as for an energy-neutral case for real-time, TOU and flat rates. Employing energy use predictions from the model, increased energy use results in increased emissions in almost all cases. For the energy-neutral case, time-differentiated rates increase CO₂ as compared to flat rates, and the TOU rate causes a larger increase than does real-time pricing. But both rates decrease other emissions in the majority of years, particularly SO₂ In addition, time-differentiated rates reduce NOx potency by shifting it to non-daylight hours when conditions for the formation of smog are less favorable. Our application leads to the conclusion that the effect of the rates on emissions must consider total energy use as well as the shift from peak to off-peak. Furthermore, the predictions require consideration of the generating mix at a more detailed level than was contained in previous studies.     

Bayesian estimation of duration models: An application of the multiperiod probit model

The multiperiod probit model is presented and Bayesian estimation using the Gibbs sampler with data augmentation is described. As an empirical illustration, the multiperiod probit model is then used to estimate a duration model using employment duration data for the Canadian province of New Brunswick. Bayesian estimation with unobserved heterogeneity is shown to be a simple extension of estimation of a duration model with no unobserved heterogeneity. More importantly, perhaps, some numerical problems encountered by other authors using Maximum Likelihood are avoided.I would like to thank M. Baker, G. Koop, A. Melino and D. Poirier for helpful comments and discussions. I would also like to thank M. Baker for providing his data.     

Bayesian cost-effectiveness analysis for censored data: an application to antiplatelet therapy

Abstract

Objective:

Cost-effectiveness analysis (CEA) on trial-based data has played an important role in pharmacoeconomics. A regression model can be used to account for patient-level heterogeneity throughout covariates adjustment in CEA. However, the estimates from CEA could be biased if ignoring the censoring issue on effectiveness and costs. This study is to propose a regression model to account for both time-to-event effectiveness and cost.

Methods:

A bivariate regression model was proposed to analyze both effectiveness and cost simultaneously, while censored observations were also taken into account. The regression coefficients were estimated using a Bayesian approach by drawing a random sample from their posterior distribution derived from the Markov chain Monte Carlo (MCMC) method. The proposed method was illustrated using empirical data of anti-platelet therapies to the management of cardiovascular diseases for those patients with high risk of gastrointestinal (GI) bleeding, where cost-effectiveness between different therapies was analyzed under both censored and non-censored circumstances, where the effectiveness was defined as the time to re-hospitalization due to GI complications, and the cost was measured by the total drug expenditure.

Results:

Under censored circumstances, aspirin plus proton-pump inhibitors (PPIs) was considered more cost-effective than clopidogrel with/without PPIs, as shown in the cost-effectiveness acceptability curve, and clopidogrel was preferred to aspirin for a willingness-to-pay of 89 NTD for delaying 1 day to hospitalization due to GI complications.

Conclusions:

Ignoring censoring problems could possibly bias the results in CEA. This study has provided an appropriate method to conduct regression-based CEA to improve the estimation which serves its purpose for CEA concerns.

Limitations:

The normality assumption for the cost and effectiveness in the bivariate normal regression needs to be examined, and the conclusions may be biased if this assumption is violated. However, when sample size is sufficiently large, a slight deviation from normality would not be a serious problem.     

A panel data heterogeneous Bayesian estimation of environmental Kuznets curves for CO2 emissions

This article investigates the Environmental Kuznets Curves (EKC) for CO₂ emissions in a panel of 109 countries during the period 1959 to 2001. The length of the series makes the application of a heterogeneous estimator suitable from an econometric point of view. The results, based on the hierarchical Bayes estimator, show that different EKC dynamics are associated with the different sub-samples of countries considered. On average, more industrialized countries show evidence of EKC in quadratic specifications, which nevertheless are probably evolving into an N-shape based on their cubic specification. Nevertheless, it is worth noting that the EU, and not the Umbrella Group led by US, has been driving currently observed EKC-like shapes. The latter is associated to monotonic income–CO₂ dynamics. The EU shows a clear EKC shape. Evidence for less-developed countries consistently shows that CO₂ emissions rise positively with income, though there are some signs of an EKC. Analyses of future performance, nevertheless, favour quadratic specifications, thus supporting EKC evidence for wealthier countries and non-EKC shapes for industrializing regions.     

Engineering robust instruments for GMM estimation of panel data regression models with errors in variables: a note

Econometricians have long recognized the need to account in some way for measurement errors, specification errors and endogeneity to ensure that the ordinary least squares estimator is consistent. This article introduces a new generalized method of moments estimator that relies on robust instruments to estimate panel data regression models containing errors in variables. We show how this GMM approach can be generalized for the panel data framework using higher moments and cumulants as instruments. The new instruments, engineered for greater robustness, are proposed to tackle the pervasive problem of weak instruments.     

Testing for structural breaks in panel varying coefficient models: with an application to OECD health expenditure

In this article, we propose a model selection approach for testing structural breaks in a semiparametric panel varying coefficient model. Monte Carlo evidence shows that the proposed model selection approach performs well in finite sample settings. Applying the method to an empirical data, we find evidence of structural breaks in Organisation for Economic Co-operation and Development (OECD) health expenditure data by allowing for income elasticity to be state (income)-dependent. The relationship between health expenditure and income is subject to two types of structural changes: smooth changes over income and structural breaks in the time dimension. The findings hold for both foreign exchange rate-converted and Purchasing Power Parity-converted expenditure and GDP.     

Inequality and development: Evidence from semiparametric estimation with panel data

Evidences from nonparametric and semiparametric unbalanced panel data models with fixed effects show that Kuznet’s inverted-U relationship is confirmed when economic development reaches a threshold. The model tests justify semiparametric specification. The integrated net contribution of control variables to inequality reduction is significant.     

Dynamic panel data models: a guide to micro data methods and practice

This paper reviews econometric methods for dynamic panel data models, and presents examples that illustrate the use of these procedures. The focus is on panels where a large number of individuals or firms are observed for a small number of time periods, typical of applications with microeconomic data. The emphasis is on single equation models with autoregressive dynamics and explanatory variables that are not strictly exogenous, and hence on the Generalised Method of Moments estimators that are widely used in this context. Two examples using firm-level panels are discussed in detail: a simple autoregressive model for investment rates; and a basic production function.JEL Classification: C23This paper is prepared for a special issue of the Portuguese Economic Journal. My understanding of this subject has benefitted immeasurably from the input of colleagues, notably Manuel Arellano, Richard Blundell, Costas Meghir, Steve Nickell and Frank Windmeijer. I thank Joao Santos Silva, Frank Windmeijer and other participants at the Cemmap/ESRC Econometric Study Group workshop in London on 22 February 2002 for detailed comments on an earlier draft. Financial support from the ESRC Centre for the Microeconomic Analysis of Public Policy is gratefully acknowledged.     

Endogeneity in panel stochastic frontier models: an application to the Japanese cotton spinning industry

We present a panel stochastic frontier model that handles the endogeneity problem. This model can treat the endogeneity of both frontier and inefficiency variables. We apply our method to examine the technical efficiency of Japanese cotton spinning industry. Our results indicate that market concentration is endogenous, and when its endogeneity is properly handled, it has a larger negative impact on the technical efficiency of cotton spinning plants. We find that the exogenous model substantially overestimates efficiency in concentrated markets.     

Three-dimensional panel data models with interactive effects: Estimation and simulation

This paper considers three-dimensional panel data models with unobservable multiple interactive effects, which are potentially correlated with the covariates. We propose an iterated OLS (IOLS) approach for the estimation of the static model and an iterated GMM (IGMM) method for the dynamic model. Monte Carlo simulations illustrate that our methods perform well in finite samples.     

Median-unbiased estimation of structural change models: an application to real exchange rate persistence

Measuring deviations from purchasing power parity has been the subject of extensive investigation. The most common practice in empirical research for measuring real exchange rate persistence is to estimate univariate autoregressive (AR) time series models and calculate the half-life, defined as the number of periods for a unit shock to a time series to decay by 50%. In the presence of structural change, there are two potential biases in the parameter estimates of AR models: (1) a downward small sample median-bias and (2) an upward bias, which occurs when structural change is present and ignored. We conduct a variety of Monte Carlo simulations and demonstrate that the existence of structural change causes a substantial increase in the small sample bias documented in Andrews (1993). We then propose an extension of median-unbiased estimation, which explicitly accounts for structural change, and apply these methods to estimate half-lives of several long-horizon real exchange rates analysed by Lothian and Taylor (1996) and Taylor (2002). The upward bias from neglecting structural change dominates the downward median-bias for these real exchange rates. When structural change is present and accounted for, the median-unbiased half-lives towards a changing mean decrease and the confidence intervals tighten.     

Simulation-based inference in dynamic panel probit models: An application to health

This paper considers the determinants of a binary indicator for the existence of functional limitations using seven waves (1991–1997) of the British Household Panel Survey (BHPS). The focal point of our analysis is the contributions of state dependence, heterogeneity and serial correlation in explaining the dynamics of health. To investigate these issues we apply static and dynamic panel probit models with flexible error structures. To estimate the models we use maximum simulated likelihood (MSL) with antithetic acceleration and implement a recently proposed test for the existence of asymptotic bias. The dynamic models show strong positive state dependence. Data from the British Household Panel Survey (BHPS) were supplied by the ESRC Data Archive. Neither the original collectors of the data nor the Archive bear any responsibility for the analysis or interpretations presented here. Funding was provided by the ESRC award no: R000238169-Simulation-based econometric approaches to investigating the interaction of lifestyle and health. The authors would like to thank William Greene for valuable comments on an earlier draft of the paper, Roberto Leon Gonzalez for valuable programming advice, and participants at the iHEA Third International conference, York, 22–25 July 2001 and York Seminars in Health Econometrics (YSHE) for their comments.     

The behavior of Turkish exchange rates: A panel data perspective

This paper investigates the behavior of Turkish exchange rates within the context of purchasing power parity (PPP) hypothesis by means of recent developments in the panel unit root testing procedures for ten Turkish real exchange rates during January 2002–May 2012. The unit root test which accounts for nonlinearity, smooth structural shifts, and cross-section dependency supports that PPP hypothesis holds for Eurozone and European countries (Denmark, Norway, Sweden, Switzerland, and United Kingdom), while it does not hold for non-European trading partners (Canada, Japan, Saudi Arabia, and USA). From the empirical results, we can conclude that PPP hypothesis holds in the countries which have the free trade agreement, while it is violated in the countries in which there are trade barriers and greater distance. The findings therefore provide policy implications for Turkey in determining equilibrium exchange rates with her major trading partners.     

Multidimensional welfare distributions: empirical application to household panel data from Vietnam

This article explores the empirical application of theoretical multidimensional welfare distribution analysis techniques to real household welfare distributions. The article operationalizes recent conceptual developments in multidimensional distribution theory and assesses their usefulness for the measurement of multidimensional household inequality. The results strongly highlight the importance of bringing nonmonetary aspects of household welfare into the forefront of inequality analysis. Agreement over the various approaches to the measurement of multidimensional inequality entails, however, nontrivial decisions that may limit the practical usefulness of these measures. We suggest that the use of multidimensional inequality ranges and the application of restrictive dominance criteria to multidimensional welfare distributions may open significant scope for further developments in the empirical analysis of multidimensional inequality.     

Nonlinearity in real exchange rates: an approach with disaggregated data and a new linearity test

Employing disaggregated real exchange rates from nine European counties in 16 goods categories, we assess in this study the nonlinearity in the real exchange rates. Surprisingly, we find evidence for nonlinearity in only four (10) out of 143 series with the linearity test proposed by Harvey et al. (2008 Harvey, D. I., Leybourne, S. J. and Xiao, B. 2008. A powerful test for linearity when the order of integration is unknown. Studies in Nonlinear Dynamics and Econometrics, 12 Art 8[Web of Science ®] , [Google Scholar]) at the 5% (10%) significance level. This result differs greatly from those of Juvenal and Taylor (2008 Juvenal, L. and Taylor, M. P. 2008. Threshold adjustment of deviations from the law of one price. Studies in Nonlinear Dynamics and Econometrics, 12 Art 8[Web of Science ®] , [Google Scholar]), Imbs et al. (2003 Imbs, J., Mumtaz, H., Raven, M. O. and Rey, H. 2003. Nonlinearities and real exchange rate dynamics. Journal of the European Economic Association, 1: 639–49. [Crossref] , [Google Scholar]), Sarno et al. (2004 Sarno, L., Taylor, M. P. and Chowdhury, I. 2004. Nonlinear dynamics in deviations from the law of one price: a broad-based empirical study. Journal of International Money and Finance, 23: 1–25. [Crossref], [Web of Science ®] , [Google Scholar]) and Berka (2009 Berka, M. 2009. “Non-linear adjustment in law of one price deviations and physical characteristic of good”. In Review of International Economics Vol. 17, 51–73.  [Google Scholar]), who report ample evidence for nonlinearity for the same or similarly disaggregated real exchange rate datasets.     

Games of strategic complementarities: an application to Bayesian games

This paper provides an introduction to the theory of games of strategic complementarities, considers Bayesian games, and provides an application to global games. This paper is based on the Spanish Economic Review lecture given at the Simposio de Análisis Económico, Alicante, December 2001. Support from the Spanish Ministry of Education and Science (project SEJ2005-08263) is gratefully acknowledged.     

Demand for cigarettes in Turkey: an application of count data models

Household cigarette demand in Turkey is examined using the zero-inflated negative binomial model to account for a large portion of households not reporting cigarette smoking or purchase and estimated using the data from the national household survey implemented in 2003. Data were divided into two main groups: families with and without teenagers. Results identify relevant household head and household characteristics needed to develop effective public policy to prevent the decision to begin to smoke and to reduce cigarette purchase to lower the future growth of government healthcare expenditures. Specifically, healthcare expenditure share, income, and cigarette-price elasticities are relevant in lowering cigarette purchases. The calculated price elasticities for cigarette demand falls within the range determined by studies conducted for developed countries including the member states of the European Union. An estimate of the effect of an increase in the excise tax lowering demand is provided.