Re-examining the real interest rate parity hypothesis (RIPH) using panel unit root tests with asymmetry and cross-section dependence

This paper investigates the validity of the real interest rate parity hypothesis (RIPH) using a panel unit root approach. For this purpose, first we estimate the possible nonlinear data-generating processes of the real interest rate differential series and using these estimates determine which panel unit root test is better for analyzing the RIPH. To this end, smooth transition autoregressive and threshold autoregressive (TAR) models are estimated for two different panels of countries: G7 and post-Soviet transition economies. The results show that the data displays both strong asymmetry and high transition speed. Therefore, secondly, we propose a new panel unit root test where the alternative is stationary with asymmetric TAR adjustment, and provide their empirical power properties. Finally, we demonstrate that our newly proposed test is able to provide conclusive evidence in favor of the RIPH in contrast to the other panel unit root tests considered.     

Capital flows and current account dynamics in Turkey: A nonlinear time series analysis

The paper offers an analysis of current account dynamics and its sustainability in Turkey using quarterly data. The focus is on the nonlinear characterization of the long run intertemporal budget constraint and the stationarity tests. Several well-known tests are applied to identify nonlinearity in the current account time series. The analysis reveals that while the classical unit root tests based on linear specification give rise to conflicting results as to the nonstationarity of the current account deficit series, a threshold unit root test due to Caner and Hansen (2001) fails to reject the null of nonstationarity, implying that the intertemporal budget constraint would not be satisfied in the long run.     

Modelling movie attendance with seasonality: evidence from China

High-frequency data improves the timeliness of movie attendance forecasts, but also results in the issue of seasonality. The main objective of this article is to build and test a novel movie attendance model that considers seasonality. Based on the Bass model, we combine an intertemporal demand shift pattern and the binary elements of seasonality – weekends and holidays – and propose a model called DISBM. We chose a sample of 58 movies released in China in 2013 to evaluate our proposal. The empirical results suggest that DISBM has better performance than other seasonal models. We demonstrate that the intertemporal demand shift results in weekend fluctuations, while the extra demand causes the seasonal holiday effect. The intent of this study is to better understand various movie attendance diffusions given different seasonal effects, in order to develop corresponding marketing strategies.     

A convenient test of functional form for pooled econometric models

This paper demonstrates a parametric test of specification that can be used in validating econometric models employing pooled time series and cross-section data with fixed effects. This Lagrange multiplier test allows for the simultaneous testing of proper model functional form and the presence of nonspherical disturbances, using a combination of the Box-Cox transformation, the double-length regression of Davidson and MacKinnon, and the Bonferroni inducedt-test. Testing procedures are demonstrated using a model of long distance telephone demand in the United States. The illustrative model used is representative of models filed as direct testimony by telephone companies in administrative law proceedings, which usually require rigorous model validation and defenses of model results in a formal hearing room setting. The tests presented in this paper are useful to a wide variety of researchers who use pooled econometric models with fixed effects in their work.     

ARE LABOUR FORCE PARTICIPATION RATES NON‐STATIONARY? EVIDENCE FROM 130 YEARS FOR G7 COUNTRIES*

This paper applies a unit root test with a non‐linear threshold to examine whether labour force participation rates are mean reverting for G7 countries using annual data over a 130 year period. We find some evidence of mean reversion for just over half the sample; however, this result is sensitive to regime shifts. We also examine whether the labour force participation rate is trend reverting through employing a lagrange multiplier (LM) unit root test with one and two structural breaks in the intercept and slope. The LM unit root test provides no additional evidence in support of stationarity. On the basis of the unit root tests for mean reversion we conclude that there is at best mixed evidence that long‐term changes in unemployment rates translate into long‐term changes in employment rates and that the unemployment rate is a useful indicator of joblessness.     

Forecasting Dutch GDP and inflation using alternative factor model specifications based on large and small datasets

We compare the factor forecasting performance of nested specifications of the generalized factor model based on various configurations of a large macroeconomic data set. The forecast simulation design involves in-sample model selection, factor estimation, parameter estimation and, finally, generating factor forecasts and factor augmented autoregressive forecasts. To empirically determine the importance of the size and the structure of the data set, we run the forecast simulation design for different configurations of the data set. We compare the factor model diagnostics of each specification and data configuration with the corresponding forecast performance. The results favour the factor structure as the specification that imposes the factor structure to the least extent and, hence, is allowed most flexibility to adapt to the data, is significantly being outperformed. Moreover, the results show that size matters as though smaller macroeconomic data sets exhibit stronger coherence, the factors being well fit, however, generally do not show improved forecasting performance.     

International Telecommunications Forecasting: an Investigation of Alternative Functional Forms

This paper provides an investigation of alternative models of international telecommunications traffic for several of the main streams emanating from Australia. Specifically, several alternative functional forms are compared with the standard double-log specification so often used in such studies. The motivation for such a study is twofold. In the first place, the double-log specification generates elasticities that are constant over time. Given the intertemporal changes in the budget share of telecommunications, this may not be a resonable formulation. The second motivation derives from teh need to use the demand models to forecast. Although the double-log model may provide a good within-sample fit, this is no gurantee that it will provide good post-sample forecasts.     

The analysis of consumer demand in Greece. Model selection and dynamic specification

The paper analyses the pattern of consumer demand in Greece exploring systematically the questions of the functional form of demand that best fits the data, the appropriate dynamic structure and the empirical validity of the constraints of demand theory. A general dynamic Almost Ideal demand model for four categories of consumer non-durables for the period 1958–1994 is estimated. The maintained specification rejects the static AI, its counterparts implied by the partial adjustment and autoregressive disturbances models and, upon applying a non-nested test, the Rotterdam specification. However, it cannot reject homogeneity and symmetry nor the hypothesis of structural stability.     

A nonlinear approach to testing the unit root null hypothesis: an application to international health expenditures

In this article, we examine the unit root null hypothesis for per capita total Health Expenditures (HEs), per capita private HEs and per capita public HEs for 29 Organization for Economic Co-operation and Development (OECD) countries. The novelty of our work is that we use a new nonlinear unit root test that allows for one structural break in the data series. We find that for around 45% of the countries, we are able to reject the unit root hypothesis for each of the three HE series. Moreover, using Monte Carlo simulations, we show that our proposed unit root model has better size and power properties than the widely used Augmented Dickey–Fuller (ADF) and Lagrange Multiplier (LM) type tests.     

Estimating and testing the compensated double-log demand model

In spite of the proliferation of flexible functional forms for consumer demand systems, the double-log demand model continues to be popular, especially in applied work calling for single-equation models. It is usually estimated in uncompensated form. It can also be estimated in compensated form, by deflating the income variable alone using Stone's price index. The compensated form has the same right-hand side as a single-equation version of the popular linear approximation to the Almost Ideal demand model, facilitating the construction of a test for choosing between the two alternatives. This paper demonstrates these results, develops the specification test, and illustrates its application using US meat consumption data. Simulations suggest that the test is well-behaved with good power in typical applications.     

THE AGRICULTURAL TERMS OF TRADE IN BANGLADESH: AN ECONOMETRIC ANALYSIS OF TRENDS AND MOVEMENTS, 1952–2006

This paper investigates the trends and movements of agricultural prices, industrial prices and the agricultural terms of trade in Bangladesh with annual data for the period 1952–2006. The ADF and KPSS tests results suggest that both agricultural and industrial prices have a unit root while the agricultural terms of trade is trend-stationary. These results remain unchanged if allowance is made in the unit root test for the possibility of a structural break during 1971–1975 (when Bangladesh gained independence from Pakistan and experienced economic shocks) by applying the two-step procedure of Perron (1989 ). A simple Nerlovian agricultural price determination model is specified within the framework of aggregate demand and aggregate supply. The Johansen cointegration test results for the periods 1953–2006 and 1973–2006 suggest that there exists a cointegral relationship between agricultural prices, industrial prices, per-capita real income and the real exchange rate between the Bangladeshi taka and the US dollar under the restriction that per-capita real income and the real exchange rate are 'long-run forcing variables' in the sense of Pesaran and Shin (1995 ), and Pesaran, Shin and Smith (1996 ). The paper estimates a four-variable vector error-correction (VEC) model and conducts an impulse response analysis for the post-independence period, 1973–2006.     

The behaviour of seasonal unit root tests under neglected local drifts

This paper analyses the limit distributions of the seasonal unit root test procedures proposed by Dickey, Hasza and Fuller (1984) and Hylleberg, Engle, Granger and Yoo (1990), when local trends at different frequencies are present in data generation processes, but ignored in the test regressions used. The findings presented explicitly show that neglected deterministic trends have negative effects on the distributions of the test statistics. Analytical observations and Monte Carlo simulations reveal that seasonal unit root test statistics become severely undersized as the values of standardized local trends increase. Hence, failure to consider local trends may often bear the undesirable effect of biasing decisions towards non-rejection of unit roots.Received: February 2001, Accepted: September 2001, JEL Classification: C12, C22Paulo M. M. Rodrigues: I am thankful to two anonymous referees for their detailed and useful comments and suggestions.     

The seasonal unit root structure in New Zealand Macroeconomic variables

ADF unit root tests are generally applied to macroeconomic data prior to testing theoritical models to ensure that all relevant variables are integrated of the same order. Not only is it important to test that these variables are integrated of the same order but also that a cointegrating relationship exists; failure to do so raise the specture of false inference associated with the spurious regression problem. The seasonal nature of quarterly data adds a further proplem which has generally been overcome by seasonally adjusting the data using procedure such as the census X-11 rather than suppressing it, have attempted to determine whether the seasonal component in each variable exhibits stochastic non-stationary. This paper analysisunit roots in a seasonal setting and compares the recently developed tests for seasonal unit roots as well as the standard augmented Dickey-Fuller zerop frequency unit root tests. Of the variables tested relatively few paper to be integrated at the seasonal frequenciues and, as other studies suggest,determinstic seasonal effects are typically more important than stochastic ones.     

Time-varying U.S. inflation dynamics and the New Keynesian Phillips curve

This paper introduces a form of boundedly-rational inflation expectations in the New Keynesian Phillips curve. The representative agent is assumed to behave as an econometrician, employing a time series model for inflation that allows for both permanent and temporary shocks. The near-unity coefficient on expected inflation in the Phillips curve causes the agent's perception of a unit root in inflation to become close to self-fulfilling. In a “consistent expectations equilibrium,” the value of the Kalman gain parameter in the agent's forecast rule is pinned down using the observed autocorrelation of inflation changes. The forecast errors observed by the agent are close to white noise, making it difficult for the agent to detect a misspecification of the forecast rule. I show that this simple model of inflation expectations can generate time-varying persistence and volatility that is broadly similar to that observed in long-run U.S. data. Model-based values for expected inflation track well with movements in survey-based measures of U.S. expected inflation. In numerical simulations, the model can generate pronounced low-frequency swings in the level of inflation that are driven solely by expectational feedback, not by changes in monetary policy.     

Car ownership and use in Britain: a comparison of the empirical results of alternative cointegration estimation methods and forecasts

This paper addresses two problems faced by many forecasters in the transport sector, namely how to use a relatively small sample to forecast car ownership over a long period of time and avoid the difficulties caused by spurious or nonsense regressions. Five alternative estimation methods are used to test for cointegrating relationships between per capita car ownership (and use) and real per capita personable disposable income, real motoring costs and real bus fares. These are the Engle-Granger two-stage, the Phillips-Hansen fully modified, the Wickens-Breusch one-stage, the autoregressive distributed lag, and the Johansen maximum likelihood methods. The corresponding error correction models are estimated, and a comparison made between the derived short- and long-run demand elasticities for car ownership and use. The ex-post forecasting performance of the error correction models, together with an ARIMA model specification, is evaluated using a number of performance criteria. The long-range time series forecasts obtained from the cointegrating regressions are compared with those from the cross-sectional approach used by the UK Department of the Environment, Transport and the Regions, and the policy implications discussed.     

Further application of Narayan and Liu (2015) unit root model for trending time series

In this paper, we further subject the new GARCH-based unit root test for trending time series proposed by Narayan and Liu (NL) (2015) to empirical scrutiny. We utilize daily, weekly, and monthly data of 10-year bond yield for seventeen countries across the regions of America, Asia, and Europe. We find that the unit root test for sovereign bond yield data is better modeled in the presence of structural breaks, conditional heteroscedasticity, and time trend. More importantly, it may be necessary to pre-test for the existence of these statistical features when modeling with the bond yield data.     

Examining the evidence of purchasing power parity by recursive mean adjustment

This paper revisits the empirical evidence of purchasing power parity under the current float by recursive mean adjustment (RMA) proposed by So and Shin (1999). We first report superior power of the RMA-based unit root test in finite samples relative to the conventional augmented Dickey–Fuller (ADF) test via Monte Carlo experiments for 16 linear and nonlinear autoregressive data generating processes. We find that the more powerful RMA-based unit root test rejects the null hypothesis of a unit root for 16 out of 20 current float real exchange rates relative to the US dollar, while the ADF test rejects only 5 at the 10% significance level. We also find that the computationally simple RMA-based asymptotic confidence interval can provide useful information regarding the half-life of the real exchange rate.     

Error-correction based panel estimates of the demand for money of selected Asian countries with the extreme bounds analysis

This paper uses the extreme bounds analysis (EBA) of Leamer (1983, 1985) to analyze the robust determinants of the demand for money in a panel of 17 Asian countries for the period 1970 to 2009. These robust determinants are found to be unit root variables. Therefore, cointegration between these variables is tested with a recent time series panel method developed by Westerlund (2007). This method uses the error-correction formulation and has more power against the null of no cointegration. The results show that there is a well-defined long-run demand for money. Using the lagged error correction term from the estimated cointegrating equation, the short-run dynamic relationships are estimated. This paper, thus, suggests some useful guidelines to estimate other relationships with panel data.     

Modelling Evolving Long-run Relationships: An Application to the Italian Energy Market

This paper considers a SUTSE model embedded in a dynamic framework to estimate an energy cost share model for the Italian economy in an evolving environment. This is achieved by allowing stochastic seasonal and trend components in the long-run specification and constructing an error correction mechanism to model short-run dynamics. Modelling instability in the structural time series approach is shown to be a very flexible approach to non conventional cointegration analysis. Tests for instability in the cointegrating regression support the evolving specification adopted.     

Was the recent downturn in US real GDP predictable?

This article uses a small set of variables – real GDP, the inflation rate and the short-term interest rate – and a rich set of models – atheoretical (time series) and theoretical (structural), linear and nonlinear, as well as classical and Bayesian models – to consider whether we could have predicted the recent downturn of the US real GDP. Comparing the performance of the models to the benchmark random-walk model by root mean-square errors, the two structural (theoretical) models, especially the nonlinear model, perform well on average across all forecast horizons in our ex post, out-of-sample forecasts, although at specific forecast horizons certain nonlinear atheoretical models perform the best. The nonlinear theoretical model also dominates in our ex ante, out-of-sample forecast of the Great Recession, suggesting that developing forward-looking, microfounded, nonlinear, dynamic stochastic general equilibrium models of the economy may prove crucial in forecasting turning points.