Nonlinearity and structural stability in the Phillips curve: Evidence from Turkey

In this paper, we investigate possible nonlinearities in the inflation–output relationship in Turkey for the 1980–2008 period. We first estimate a linear bivariate model for the inflation rate and output gap, and test for linearity of the estimated model against nonlinear alternatives. Linearity test results suggest that the relationship between the inflation rate and output gap is highly nonlinear. We estimate a bivariate time-varying smooth transition regression model, and compute dynamic effects of one variable on the other by generalized impulse response functions. Computed impulse response functions indicate that inflation–output relationship in Turkey during the analyzed period was regime dependent and varied considerably across time.     

South African stock return predictability in the context data mining: The role of financial variables and international stock returns

In this paper, we examine the predictive ability, both in-sample and the out-of-sample, for South African stock returns using a number of financial variables, based on monthly data with an in-sample period covering 1990:01 to 1996:12 and the out-of-sample period of 1997:01 to 2010:04. We use the t-statistic corresponding to the slope coefficient in a predictive regression model for in-sample predictions, while for the out-of-sample, the MSE-F and the ENC-NEW tests statistics with good power properties were utilised. To guard against data mining, a bootstrap procedure was employed for calculating the critical values of both the in-sample and out-of-sample test statistics. Furthermore, we use a procedure that combines in-sample general-to-specific model selection with out-of-sample tests of predictive ability to further analyse the predictive power of each financial variable. Our results show that, for the in-sample test statistic, only the stock returns for our major trading partners have predictive power at certain short and long run horizons. For the out-of-sample tests, the Treasury bill rate and the term spread together with the stock returns for our major trading partners show predictive power both at short and long run horizons. When accounting for data mining, the maximal out-of-sample test statistics become insignificant from 6-months onward suggesting that the evidence of the out-of-sample predictability at longer horizons is due to data mining. The general-to-specific model shows that valuation ratios contain very useful information that explains the behaviour of stock returns, despite their inability to predict stock return at any horizon. The model also highlights the role of multiple variables in predicting stock returns at medium- to long run horizons.     

Does measurement error matter in volatility forecasting? Empirical evidence from the Chinese stock market

Based on methods developed by Bollerslev et al. (2016), we explicitly accounted for the heteroskedasticity in the measurement errors and for the high volatility of Chinese stock prices; we proposed a new model, the LogHARQ model, as a way to appropriately forecast the realized volatility of the Chinese stock market. Out-of-sample findings suggest that the LogHARQ model performs better than existing logarithmic and linear forecast models, particularly when the realized quarticity is large. The better performance is also confirmed by the utility based economic value test through volatility timing.     

A note on tests of sphericity and cross-sectional dependence for fixed effects panel model

This paper theoretically explains why bias correction appears in two statistics recently developed by Baltagi et al. (2011, 2012), which are designed to test the sphericity and cross-sectional dependence of the errors in the fixed effects panel model respectively. Our explanation shows that the bias correction is in fact avoidable, which is demonstrated by two corresponding statistics that are newly constructed in this paper. Simulation suggests that our statistics perform as well as the two in Baltagi et al. (2011, 2012). In addition, according to the theories underlying our explanation, we extend a new sphericity test proposed by Fisher et al. (2010) to the fixed effects model. Simulation finds that the test behaves well only if both the cross-sectional and the time series dimension are large.     

Threshold effects in panel data stochastic frontier models of dairy production in Canada

One of the most enduring problems in econometrics is how to properly account for heterogeneity among firms. Threshold regression models are intuitively appealing methods to deal with this issue. We consider a fixed-effect panel data stochastic frontier model (Schmidt and Sickles, 1984; Martin-Marcos and Suarez-Galvez, 2000) and, relying on Hansen (1999, 2000a), we propose an estimator that accommodates multiple thresholds. Our model assumes absence of any unmeasured time invariant heterogeneity across firms as in Greene (2005, p. 277). Slope and threshold parameters can be estimated using a within estimator combined with a grid search over the threshold parameters. Testing for threshold effects is problematic because threshold parameters are not identified under the null hypothesis, a case of the so-called Davies' problem. We apply the bootstrap procedure proposed by Hansen (1999, 2000a) to test for the presence of thresholds. An asymptotic confidence set for the threshold parameter can be obtained by inverting an LR test, using the distribution result presented in Hansen (1999, 2000a). Our empirical application features a panel of Quebec dairy farms. We use farm size as the threshold variable. The presence of a trend in the specification matters for the determination of the number of thresholds. Technical efficiency scores and rankings of farms estimated from competing model specifications are highly correlated and do not vary significantly across groups of farm sizes defined by the threshold parameter values.     

TESTING FOR STATIONARITY IN HETEROGENEOUS PANEL DATA IN THE CASE OF MODEL MISSPECIFICATION

This paper investigates the performance of the tests proposed by Hadri and by Hadri and Larsson for testing for stationarity in heterogeneous panel data under model misspecification. The panel tests are based on the well known KPSS test (cf. Kwiatkowski et al.) which considers two models: stationarity around a deterministic level and stationarity around a deterministic trend. There is no study, as far as we know, on the statistical properties of the test when the wrong model is used. We also consider the case of the simultaneous presence of the two types of models in a panel. We employ two asymptotics: joint asymptotic, T, N →∞ simultaneously, and T fixed and N allowed to grow indefinitely. We use Monte Carlo experiments to investigate the effects of misspecification in sample sizes usually used in practice. The results indicate that the assumption that T is fixed rather than asymptotic leads to tests that have less size distortions, particularly for relatively small T with large N panels (micro‐panels) than the tests derived under the joint asymptotics. We also find that choosing a deterministic trend when a deterministic level is true does not significantly affect the properties of the test. But, choosing a deterministic level when a deterministic trend is true leads to extreme over‐rejections. Therefore, when unsure about which model has generated the data, it is suggested to use the model with a trend. We also propose a new statistic for testing for stationarity in mixed panel data where the mixture is known. The performance of this new test is very good for both cases of T asymptotic and T fixed. The statistic for T asymptotic is slightly undersized when T is very small (≤10).     

External validation of the use of vignettes in cross-country health studies

Cross-country comparisons of subjective assessments are rendered difficult if not impossible because of sub-population specific response style. To correct for this, the use of vignettes has become increasingly popular, notably within cross-country health studies. However, the validity of vignettes as a means to re-scale across sample sub-populations critically rests on the assumption of “response consistency” (RC): that vignettes and self-assessments are evaluated on the same scale. In this paper, we seek to test this assumption by applying objective measures of health along with subjective measures and vignettes. Our results indicate that the assumption of RC is not innocuous and that our extended model relaxing this assumption improves the fit and significantly changes the cross-country rankings of health vis-á-vis the standard Chopit model.     

Can we reject linearity in an HAR-RV model for the S&P 500? Insights from a nonparametric HAR-RV

This article tests the linearity assumption underlying the popular heterogeneous autoregressive model for realized volatility (HAR-RV). We implement a consistent model specification test that is robust to both distributional and model misspecification. We find that, using a nonparametric HAR-RV (NPHAR-RV), we are unable to reject the null of linearity.     

Bargaining and network structure: An experiment

We consider bargaining in a bipartite network of buyers and sellers, who can only trade with the limited number of people with whom they are connected. We perform an experimental test of a graph-theoretic model that yields unique predictions about equilibrium prices for the networks in our sessions. The results diverge sharply depending on how a connection is made between two separate simple networks, typically conforming to the theoretical directional predictions. Payoffs can be systematically affected even for agents who are not connected by the new link, and we find evidence of a form of social learning.     

Technological differences and convergence in the OECD

Abstract. In this paper we test the homogeneity of the technological parameters among OECD countries, which is the maintained hypothesis in most of the empirical growth literature. We first identify differences in the constant term of the convergence equation estimated for the OECD 1960/1990 sample using a fixed- effects estimator. Then we provide a formal test of the homogeneity of technological parameters across groups of countries. We identify at least two different groups within the OECD, with significantly different technologies. Convergence within each group is fast, supporting the notion of club convergence. Nevertheless, the implausible parameter values obtained for the leading technology club casts some doubts on the validity of the Solow model to account for the long run behaviour of this group of countries.     

A simple and effective misspecification test for the double-hurdle model

The commonly-used version of the double-hurdle model rests on a rather restrictive set of statistical assumptions, which are very seldom tested by practitioners, mainly because of the lack of a standard procedure for doing so, although violation of such assumptions can lead to serious modelling flaws. We propose here a bootstrap-corrected conditional moment portmanteau test which is simple to implement and has good size and power properties.     

Some cautions on the use of nonlinear panel unit root tests: Evidence from a modified series-specific non-linear panel unit-root test

The purpose of this paper is to examine the relevance of applying nonlinear panel unit root test to examine the non-linear mean reversion behaviors of real exchange rates. We find that nonlinear panel unit root test may achieve lower power performance as compared to its alternative of linear panel unit test when the data generating process does not contain significant non-linear components. This finding post cautions to researchers in modeling and testing real exchanges behavior. We also develop a modified series-specific nonlinear panel unit root test and find evidence in favor of purchasing power parity hypothesis for China's four ASEAN trading partners in the period of February 1997 to August 2009.     

On the distributional effects of income in an aggregate consumption relation

Abstract .  In this paper we analyse the influence of characteristics of the income distribution in modelling aggregate consumption expenditure. We model the aggregate consumption relation of a heterogeneous population, using a statistical distributional approach of aggregation, and apply it to UK-Family Expenditure Survey data. A bootstrap test based on a non-parametric estimation methodology, which accounts for the presence of continuous and discrete variables, suggests that the mean and the dispersion of the income distribution significantly influence aggregate consumption expenditure. Also, the parameters of the aggregate relation are time varying. These findings have implications for constructing empirically sound models of aggregate consumption expenditure.     

TESTING THE SEQUENTIAL LOGIT MODEL AGAINST THE NESTED LOGIT MODEL*

In this paper, we show that the sequential logit (SL) model, in which a choice process is characterized as a sequence of independent multinomial logit models, is a limiting case of the nested logit (NL) model. For testing the SL model against the NL model, we propose Wald, likelihood ratio and Lagrange multiplier tests after suitably reparameterizing the NL model. It is found that when the NL model parameters are “weakly identified”, the Wald test severely underrejects the true model, whereas the sizes of the LR and LM tests are not significantly affected.     

A Comparison of Alternative Non-parametric Estimators of the Short Rate Diffusion Coefficient

In this paper we discuss the estimation of the diffusion coefficient in one-factor models for the short rate via non-parametric methods. We test the estimators proposed by Ait-Sahalia (1996) , Stanton (1997) and Bandi and Phillips (2003) on Monte Carlo simulations of the Vasicek and CIR model. We show that the Ait-Sahalia estimator is not applicable for values of the mean reversion coefficient typically displayed by interest rate data, while the Stanton and Bandi–Phillips estimators perform better. Each of the three estimators depends crucially on the choice of the bandwidth parameter. Our analysis shows that the estimators give different results for both the data set analysed by Ait-Sahalia (1996) and by Stanton (1997) . Finally we show that the data sets used by Ait-Sahalia and Stanton are inherently different and, in particular, that very short-term data exhibit characteristics which are inconsistent with a diffusion.     

Testing for joint significance in nonstationary binary choice model

This paper investigates the test of joint significance for binary choice model with multiple integrated explanatory variables. It is found that for the widely used logit and probit models, even though the estimators have a different convergence rate under null hypothesis compared with the case under alternative, the commonly used Wald statistic is still useful, and asymptotically chi-squared.     

Cheating to win: Dishonesty and the intensity of competition

We argue that the intensity of competition within a group or organization can have an important influence on whether or not people cheat. To make this point we first work through a simple model of strategic misreporting in the workplace. For low and high levels of competition we show that, in equilibrium, few are predicted to misreport. It is for medium levels of competition that misreporting is predicted to be highest. We test this prediction experimentally and find good support for it. This finding has implications for the design of incentive structures within groups and organizations.     

Bidding behavior in asymmetric auctions: An experimental study

We review an asymmetric auction experiment. Based on Plum (Int. J. Game Theory 20 (1992) 393) private valuations of the two bidders are independently drawn from distinct but commonly known distributions, one of which first-order stochastically dominates the other. We test the qualitative properties of that model of asymmetric auctions, in particular whether the weak bidder behaves more aggressively than the strong, and then test bidders’ preference for first- vs. second-price auctions.     

An inter-temporal general equilibrium analysis of the Australian age pension means test

The Australian age pension is somewhat unusual among developed countries in that it is means tested against both the claimant’s income and assets. While means testing of age pensions facilitates the aims of directing public pensions to those senior individuals most in need and of containing pension expenditures by governments, it also has the effect of changing the incentives of individuals to work and save. This paper examines the implications of the Australian means tested age pension for incentives of individuals to save and work, for government financial commitments and for the welfare of individuals. To this end, we develop an overlapping generations model of the Australian economy that incorporates the essential features of the Australian pension, superannuation and taxation policy settings and use it to explore the implications of several hypothetical policy changes that relax the means test of the age pension. Our results confirm that the existing means-tested, age pension represents a disincentive for some older Australians to work.     

A simple panel stationarity test in the presence of serial correlation and a common factor

This paper develops a simple test à la Pesaran (2007) for the null hypothesis of stationarity in heterogeneous panel data with cross-sectional dependence in the form of a common factor in the disturbance. We also allow for serial correlation.