TESTING PARAMETER CONSTANCY AND SUPER EXOGENEITY IN ECONOMETRIC EQUATIONS

The paper is concerned with testing super exogeneity in a single equation that can either be linear or partially nonlinear. A joint test for testing both weak exogeneity and a form of invariance, which together amount to a form of super exogeneity, is presented and its properties discussed. The considerations also include testing parameter constancy and modelling parameter nonconstancy by an example in which testing super exogeneity in a consumption function for Norway, based on a previously published model is considered. The results are compared with the previous conclusions and found not to disagree with them.     

A component model for dynamic correlations

We propose a model of dynamic correlations with a short- and long-run component specification, by extending the idea of component models for volatility. We call this class of models DCC-MIDAS. The key ingredients are the Engle (2002) DCC model, the Engle and Lee (1999) component GARCH model replacing the original DCC dynamics with a component specification and the Engle et al. (2006) GARCH-MIDAS specification that allows us to extract a long-run correlation component via mixed data sampling. We provide a comprehensive econometric analysis of the new class of models, and provide extensive empirical evidence that supports the model’s specification.     

Testing the exogeneity specification in the complete dynamic simultaneous equation model

It is shown that in the complete dynamic simultaneous equation model exogenous variables cause endogenous variables in the sense of Granger (1969) and satisfy the criterion of econometric exogeneity discussed by Sims (1977a), but that the stationarity assumptions invoked by Granger and Sims are not necessary for this implication. Inference procedures for testing each implication are presented and a new joint test of both implications isderived. Detailed attention is given to estimation and testing when the error vector of the final form of the complete dynamic simultaneous equation model is both singular and serially correlated. The theoretical points of the paper are illustrated by testing the exogeneity specification in a small macroeconometric model.     

Testing of Fractional Cointegration in Macroeconomic Time Series*

We propose in this article a two‐step testing procedure of fractional cointegration in macroeconomic time series. It is based on Robinson's (Journal of the American Statistical Association, Vol. 89, p. 1420) univariate tests and is similar in spirit to the one proposed by Engle & Granger (Econometrica, Vol. 55, p. 251), testing initially the order of integration of the individual series and then, testing the degree of integration of the residuals from the cointegrating relationship. Finite‐sample critical values of the new tests are computed and Monte Carlo experiments are conducted to examine the size and the power properties of the tests in finite samples. An empirical application, using the same datasets as in Engle & Granger (Econometrica, Vol. 55, p. 251) and Campbell & Shiller (Journal of Political Economy, Vol. 95, p. 1062), is also carried out at the end of the article.     

Exogeneity in structural equation models

The practical relevance of several concepts of exogeneity of treatments for the estimation of causal parameters based on observational data are discussed. We show that the traditional concepts, such as strong ignorability and weak and super-exogeneity, are too restrictive if interest lies in average effects (i.e. not on distributional effects of the treatment). We suggest a new definition of exogeneity, KL-exogeneity. It does not rely on distributional assumptions and is not based on counterfactual random variables. As a consequence it can be empirically tested using a proposed test that is simple to implement and is distribution-free.     

Exogeneity in Vector Error Correction Models with Purely Exogenous Long-Run Paths

Existing exogeneity conditions of literature are only sufficient and imply 'overly strong' constraints on long-run parameters. This paper presents some new results on exogeneity in vector error correction models. A key concept of the analysis is the 'purely exogenous long-run path', i.e. a cointegrating vector only including 'exogenous' variables. Extending earlier results of Johansen, S. (1992). 'Cointegration in partial systems and the efficiency of single-equation analysis', Journal of Econometrics , Vol. 52, pp. 389–402 and of Toda and Phillips (1991) . Vector Autoregressions and Causality , Cowles Foundation Discussion Paper, No. 977 among others, we propose a framework based on two canonical representations of the long-run matrix, which can constitute a suitable basis to formulate a necessary and sufficient condition for non-causality as well as a condition for strong exogeneity. An interesting property is that the statistics involved in the sequential procedures for testing these conditions are distributed as χ ² variables and can, therefore, easily be calculated with the usual statistical computer packages, which makes our approach fully operational, empirically. Finally, the power and size distortions of the sequential test procedures are analysed using Monte Carlo experiments.     

The Impact of Risk Management Standards on Patient Safety: The Determinants of MRSA Infections in Acute NHS Hospitals, 2001–08*

We study a key part of National Health Service (NHS) policy to ensure high‐quality health care: failure to supply such care cost the NHS £787m in clinical negligence payouts during 2009–10. The NHS uses risk management standards to incentivize care, and we examine their effects on methicillin resistant Staphylococcus aureus (MRSA) infections. Using a specially assembled data set, our GMM results suggest that improvements in the risk management standards attained by some hospitals are correlated with reductions in their MRSA infection rates. Moreover, the exogeneity of this relationship cannot be rejected for higher risk management levels, suggesting attainment of higher standards was instrumental in reducing infection rates.     

Copula-based multivariate GARCH model with uncorrelated dependent errors

Multivariate GARCH (MGARCH) models are usually estimated under multivariate normality. In this paper, for non-elliptically distributed financial returns, we propose copula-based multivariate GARCH (C-MGARCH) model with uncorrelated dependent errors, which are generated through a linear combination of dependent random variables. The dependence structure is controlled by a copula function. Our new C-MGARCH model nests a conventional MGARCH model as a special case. The aim of this paper is to model MGARCH for non-normal multivariate distributions using copulas. We model the conditional correlation (by MGARCH) and the remaining dependence (by a copula) separately and simultaneously. We apply this idea to three MGARCH models, namely, the dynamic conditional correlation (DCC) model of Engle [Engle, R.F., 2002. Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business and Economic Statistics 20, 339–350], the varying correlation (VC) model of Tse and Tsui [Tse, Y.K., Tsui, A.K., 2002. A multivariate generalized autoregressive conditional heteroscedasticity model with time-varying correlations. Journal of Business and Economic Statistics 20, 351–362], and the BEKK model of Engle and Kroner [Engle, R.F., Kroner, K.F., 1995. Multivariate simultaneous generalized ARCH. Econometric Theory 11, 122–150]. Empirical analysis with three foreign exchange rates indicates that the C-MGARCH models outperform DCC, VC, and BEKK in terms of in-sample model selection and out-of-sample multivariate density forecast, and in terms of these criteria the choice of copula functions is more important than the choice of the volatility models.     

Two tests for strict exogeneity in a correlated random effects panel data Tobit model

This paper presents two tests for strict exogeneity of the covariates in a correlated random effects panel data Tobit model. The tests are applied in an analysis of hours of work of US women. Estimation procedures when a model does not pass a test for strict exogeneity are discussed.     

Testing of seasonal fractional integration in UK and Japanese consumption and income

The seasonal structure of quarterly UK and Japanese consumption and income is examined by means of fractionally based tests proposed by Robinson ( 1994 ). These series were analysed from an autoregressive unit root viewpoint by Hylleberg, Engle, Granger and Yoo (HEGY, 1990 ) and Hylleberg, Engle, Granger and Lee (HEGL, 1993 ). We find that seasonal fractional integration, with amplitudes possibly varying across frequencies, is an alternative plausible way of modelling these series. Copyright © 2001 John Wiley & Sons, Ltd.     

Efficient estimation of a multivariate multiplicative volatility model

We propose a multivariate generalization of the multiplicative volatility model of Engle and Rangel (2008), which has a nonparametric long run component and a unit multivariate GARCH short run dynamic component. We suggest various kernel-based estimation procedures for the parametric and nonparametric components, and derive the asymptotic properties thereof. For the parametric part of the model, we obtain the semiparametric efficiency bound. Our method is applied to a bivariate stock index series. We find that the univariate model of Engle and Rangel (2008) appears to be violated in the data whereas our multivariate model is more consistent with the data.     

恩格尔系数在我国的应用及修正研究

目前在我国,用恩格尔系数反映的居民生活水平与我国居民的实际生活水平有很大偏差。文中对恩格尔系数在我国应用的情况做了系统的分析,从社会、经济、文化方面找出存在问题的原因,并针对我国消费的特点对其进行了修正。     

Bootstrap inference in systems of single equation error correction models

We analyze OLS-based tests of long-run relationships, weak exogeneity and short-run dynamics in conditional error correction models. Unweighted sums of single equation test statistics are used for hypothesis testing in pooled systems. When model errors are (conditionally) heteroskedastic tests of weak exogeneity and short run dynamics are affected by nuisance parameters. Similarly, on the pooled level the advocated test statistics are no longer pivotal in presence of cross-sectional error correlation. We prove that the wild bootstrap provides asymptotically valid critical values under both conditional heteroskedasticity and cross-sectional error correlation. A Monte-Carlo study reveals that in small samples the bootstrap outperforms first-order asymptotic approximations in terms of the empirical size even if the asymptotic distribution of the test statistic does not depend on nuisance parameters. Opposite to feasible GLS methods the approach does not require any estimate of cross-sectional correlation and copes with time-varying patterns of contemporaneous error correlation.     

Stochastic cointegration: estimation and inference

This paper considers the estimation of a stochastically cointegrating regression within the stochastic cointegration modelling framework introduced in McCabe et al. (Stochastic cointegration: testing, 2001). A stochastic cointegrating regression allows some or all of the variables to be conventionally or heteroscedastically integrated. This generalizes Hansen's (J. Econom. 54 (1992) 139) heteroscedastic cointegrating regression model, where the dependent variable is heteroscedastically integrated, but all the regressor variables are restricted to being conventionally integrated. In contrast to conventional and heteroscedastic cointegrating regression, ordinary least-squares (OLS) estimation is shown to be inconsistent, in general, in a stochastically cointegrating regression. As a solution, a new instrumental variables (IVs) estimator is proposed and is shown to be consistent. Under a suitable exogeneity assumption, standard asymptotic inference on the stochastic cointegrating vector can be carried out based on the IV estimator. The finite sample properties of the test statistics, including their robustness to the exogeneity assumption, are examined by simulation.     

Towards causal estimates of children's time allocation on skill development

In this paper we examine how children's time allocation affects their accumulation of cognitive skill. Children's time allocation is endogenous in a model of skill production since it is chosen by parents and children. We apply a recently developed test of exogeneity to search for specifications that yield causal estimates of the impact time inputs have on child skills. The test exploits bunching in time inputs induced by a nonnegativity time constraint and it has power to detect a variety of sources of endogeneity. We find that with a sufficiently rich set of controls we are unable to reject exogeneity in our most detailed production function specifications. The estimates from these specifications indicate that active time with adult family members, such as parents and grandparents, are the most productive in generating cognitive skill.     

Do Power GARCH models really improve value-at-risk forecasts?

Traditional heteroskedastic models either rely on the specification of the conditional variance as in Bollerslev (1986) or on a direct modeling of the conditional standard deviation as in Taylor (1986). With its endogenous estimation of the optimal power transformation, the Power GARCH (PGARCH) of Ding, Granger, and Engle (1993) represents a flexible alternative that also nests the previous competing families. Building on a “dynamic” estimation and out-of-sample tests, the current paper undertakes a comparison of the three models in a value-at-risk setting. Despite existing fluctuations in the optimal power transformation obtained with the Ding, Granger, and Engle model, our empirical investigations suggest that the parameter is rarely found different from one or two. Although the volatility dynamics may switch from Taylor's to Bollerslev's specification during the life of the future contract, the measures of accuracy and efficiency used to assess the performance of VaR forecasts indicate that the additional flexibility brought by the PGARCH model provides little, if any, improvement for risk management. *** DIRECT SUPPORT *** A00DH023 00004     

HAZARDS IN IMPLEMENTING A MONETARY CONDITIONS INDEX

Some recent studies have suggested constructing a Monetary Conditions Index (or MCI) to serve as an indicator of monetary policy stance. The central banks of Canada, Sweden and Norway all construct an MCI and (to varying degrees) use it in conducting monetary policy. Empirically, an MCI is calculated as the weighted sum of changes in a short-term interest rate and the exchange rate relative to values in a baseline year. The weights aim to reflect these variables’ effects on longer-term focuses of policy — economic activity and inflation. This paper derives analytical and empirical properties of MCIs in an attempt to ascertain their usefulness in monetary policy. An MCI assumes an underlying model relating economic activity and inflation to the variables in the MCI. Several issues arise for that model, including its empirical constancy, cointegration, exogeneity, dynamics and potential omitted variables. Because of its structure, the model is unlikely to be constant or to have strongly exogenous variables, yet constancy and exogeneity are critical for the usefulness of an MCI. Empirical analyses of Canadian, Swedish and Norwegian MCIs confirm such difficulties. Thus, the value of an MCI for conduct of economic policy is in doubt.     

Agricultural exports and economic growth in Pakistan: an econometric reassessment

Agriculture sector works as backbone of Pakistan economy. In this modern era, exports work as locomotive of growth train. Pakistan earned a handsome amount through exports of agricultural raw material and refined products. This research investigates that either there is unidirectional or bidirectional association between agricultural exports and economic growth in Pakistan? For empirical investigation of relationships between economic growth and agricultural exports in Pakistan this study used most reliable econometric estimation tools, augmented Dickey–Fuller unit root test, Johansen co-integration and Engle–Granger causality tests for 45 time series annul observations from 1970 to 2014. This research winds up that Pakistan’s agricultural exports have positive but insignificant association with gross domestic product growth. It is due to the primary and raw material agricultural products exports which cannot compete in international markets due to close competitions, lower quality and dearer price. Consequently, receive a trifling amount as exports earnings; contribute slightly in national economic growth.     

A fractional cointegration analysis of Fisher hypothesis: evidence from Turkey

This paper examines the validity of Fisher hypothesis in Turkey over the period from 1990:01 through 2010:03 by using cointegration and fractional cointegration approaches. The findings from Engle and Granger cointegration test indicate that inflation and nominal interest rate series are cointegrated. Since the conventional cointegration tests do not provide strong evidence on the long run relationship, we also use fractional cointegration definition suggested by Cheung and Lai (J Bus Econ Stat 11:103–112, 1993) which requires only a mean reverting (d < 1) relationship between the series. The results from fractional cointegration tests based on GPH and Robinson methods show that inflation and nominal interest rate series are fractionally cointegrated. These findings support the validity of the Fisher hypothesis in Turkey.     

Homogeneity and endogeneity in systems of demand equations

In estimating systems of demand equations one of the right-hand-side explanatory variables, expenditure, may be endogenous in the sense that it is correlated with the equation error. If the assumption of homogeneity of degree zero in prices and nominal income is imposed on the system, it turns out it is still possible to estimate the parameters of the system even when expenditure is endogenous. The estimation procedure is simple requiring just one additional ordinary least squares regression.The paper also demostrates that a model in which homogeneity is tested with expenditure assumed exogenous is exactly equivalent to a model in which the exogeneity of expenditure is tested with homogeneity imposed. Previous tests of demand systems which have rejected the homogeneity postulate might therefore be reinterpreted instead as rejecting the hypothesis of exogeneity of expenditure with homogeneity of degree zero in prices and nominal income taken as given.