Narrow Results

To avoid spurious inferences, researchers analyzing the dimensions of uncertainty need to determine whether it is nonstationary. The degree of persistence of uncertainty also indicates the duration of the negative impact of an uncertainty shock on the economy. We use a new panel residual augmented least squares unit root test that allows for heterogeneous structural breaks in both intercepts and slopes of a series to determine the degree of persistence of the reports-based measure of uncertainty and whether it is nonstationary for 143 countries. This group of countries accounts for 99% of the world’s gross domestic product (GDP). To assess the robustness of our results, we also use recently developed univariate time-series unit root tests that allow for structural breaks and panel unit root tests that accommodate cross-sectional dependence and nonlinearity. Furthermore, an autoregressive wild bootstrap approach is utilized to examine the stationarity of the series. The results are virtually unambiguous in indicating that the reports-based measure of uncertainty is stationary in all countries considered. The results also suggest that uncertainty has a negative impact on the growth rate of GDP. The policy implications of the results are also discussed.

In this short article we examine the real convergence hypothesis in Germany with respect to the US by means of fractional integration. Using a parametric procedure due to Robinson (1994), the results show that real convergence is only achieved in this country if we take into account the presence of a structural break at World War II. The same evidence is found in other countries (like Japan, the UK and Canada) when this break is considered.

This article applies the panel stationarity test with a break proposed by Hadri and Rao (2008) to examine whether 14 macroeconomic variables of OECD countries can be best represented as random walk or stationary fluctuations around a deterministic trend. In contrast to previous studies, based essentially on visual inspection of the break type or just applying the most general break model, we use a model selection procedure based on BIC. We do this for each time series so that heterogeneous break models are allowed for in the panel. Our results suggest, overwhelmingly, that if we account for a structural break, cross-sectional dependence and choose the break models to be congruent with the data, then the null of stationarity cannot be rejected for all the 14 macroeconomic variables examined in this article. This is in sharp contrast with the results obtained by Hurlin (2004), using the same data but a different methodology.

This paper examines the underlying parity conditions upon which real interest parity (RIP) is predicted for some Asian countries relative to the U.S. and Japan over a period (1978–2009) containing significant changes using the multivariate cointegration procedure of Johansen et al. (2000) that allows for up to two pre-determined breaks. Each parity condition is examined to determine which is responsible for the rejection of RIP. The results suggest that the Fisher hypothesis is the least likely to violate RIP, whereas uncovered interest parity (UIP) appears to be most commonly violated. Stability tests suggest that the RIP relationship has been stable in most cases and that the impact of the Asian crisis and the Plaza Accord appears to be transitory, and that the RIP relationships have strengthened in the aftermath of the 1997–1998 Asian crisis.

High level of intra-regional trade and negative spillovers from competitive devaluation make exchange rate coordination extremely desirable in Asia. Employing a hypothetical Asian Currency Unit we evaluate the degree of coordination among Asian currencies. Traditional empirical tests yield little evidence of coordination among real and nominal exchange rates. However, introducing endogenously determined structural breaks to account for changes in exchange rate regimes provides more mixed evidence. While there is still little evidence for coordination in nominal terms, some degree of coordination among real rates emerges. The limited evidence for exchange rate coordination can be explained by the diverse exchange rate regimes prevailing in these economies, signaling differences in policy objectives.

This paper investigates the persistency in the ex-post real interest rates in the presence of endogenous structural breaks for Australia, Austria, Belgium, Canada, Denmark, France, Germany, Ireland, Italy, the Netherlands, New Zealand, Norway, Switzerland, the UK and the USA using seasonally adjusted quarterly data. The procedure used in this study extends the previous research in the respect of investigating degree of persistency of the ex-post real interest rates series by allowing for possible process shifts at endogenously determined more than two structural breaks dates following the principles suggested by Lumsdaine and Papell (1997). The results from the study show that real interest rates are very persistent when such breaks are not taken into account. However, the findings also indicate low persistency in real interest rates for all countries when such breaks are allowed in the data-generating process. We find that endogenously determined structural breaks substantially reduce the degree of persistency of the real interest rate series, which has important theoretical implications as well.

This paper re-examines the hypothesis of unemployment hysteresis using panel data for 11 Asian countries for the period from 1980 to 2008. This study employs a variety of panel data unit root tests recently advanced by Bai and Ng (2004), Pesaran (2007) and Chang and Song (2009). The advantage of these tests is that they are able to exploit the cross-section variations of the series. In addition to these tests, a new powerful panel stationarity test proposed by Carrión-i-Silvestre et al. (2005) is applied which exploits the cross-section variations of the series and also allows for different numbers of endogenous breakpoints in the series. Our findings stress the importance of accounting exogenous shocks in the series and provide stronger evidence against the hypothesis of unemployment hysteresis for the countries analyzed. We also discover critical economic affairs which may cause the unemployment rates to fluctuate significantly. Policy implications are proposed through our observations.

In this study, we examine the asymmetric effects of terrorism and economic growth in Pakistan over the period 1970–2016, while considering the role of capital per worker and structural breaks. We use the non-linear ARDL approach to establish the long-run association and to estimate the short-run and long-run effects accordingly. The results indicate the presence of asymmetries in both long and short run. Moreover, 1% decrease in terrorism results in an increase of per capita income by 0.02% in the long run and 0.001% in the short run. Assuming symmetry, the long run capital share is 0.47. In asymmetric relation, a 1% increase in capital share increases output by 0.55%, whereas a 1% decrease in capital stock decreases output by 0.26%. The break effects show that the years 1993 and 2004 have negative effects on growth. The vector error correction model-based causality results indicate a unidirectional causality from terrorism to per capita income. Overall, the results highlight that terrorism is growth retarding.

We investigate the presence of managerial skills in different categories of hedge funds. Our approach is more flexible that others [7, 10] since it does not make any a priori assumptions regarding the distribution of returns. We find that the Global Macro and Market Neutral funds do not follow a pure random walk. In fact, for both these models the drift parameter is statistically significant. This result rejects our initial hypothesis that hedge funds (expected-excess) returns are on average zero. Indeed, the positive intercept can be interpreted as evidence of managerial skill. We conclude that investors seeking to invest in hedge funds should consider Market Neutral funds and Global Macro funds as possible investments.

The intention of this article is to develop an instrument to overcome the limitations caused by traditional analyses and present a combined STR — Smooth Transition Regression model (EGARCH, STRIGARCH, and STR-FIEGARCH) to analyze the contagion effects of the 2008 financial crisis. The proposed instrument will aid the analysis of contagion and the impact of changes in long-term interest rates on the returns of international stock indices and forecasting, with special emphasis on the effects caused by structural breaks, persistence, and conditioned heteroscedasticity. The methodology begins with unit root tests with one and two structural breaks. In the second step, the asymmetry will be analyzed considering the STR models, which will determine the asymmetry relationship between interest rates and the long term, so that in a later step, these asymmetries will be used in the composition of a volatility estimation model, being based on the ARCH models: (i) EGARCH and (ii) FIEGARCH. This study provides a useful instrument based on modeling techniques to make the decision-making process more efficient and objective, providing a choice of instruments that assess the effect of changes in interest rates on stock market indices when influenced by falls, with structural data and better forecasting performance. The results show that the developed mixture models obtained better performance in predicting the effect or impact of changes in interest rates on stock market indices when influenced by structural breaks. STR and the ARCH family are useful instruments that make the decision-making process clearer and more objective when choosing instruments that assess the spillover effect of long-term interest rates on the profitability of international financial indices.

This study examines the effects of international trade and investment on output and tests the null hypothesis of Granger non-causality among trade, investment and economic growth in Canada. The long-run model is estimated using several single-equation and system estimators to assess the robustness of results across methodologies. The single-equation, OLSEG, GMM, DOLS, NLLS and FMOLS, estimates of the model provide consistent support for the positive and significant long-run effects of exports and investment on output. The ML system estimates cross-validate the cointegrating relationship and reinforce the positive effects of exports and investment and the negative effects of imports on output. The over-parameterized level-VAR estimates suggest unidirectional Granger-causality from exports, imports and investment each to output. The estimates of the model with structural breaks support the long-run relationship, though the evidence is not unambiguous ubiquitously across all the tests. The evidence supporting the positive and significant long-run effects overwhelms the evidence providing weak or no support for the effects of trade on output. The results underline the need for the acceleration of exports (and investment) to offset the demand-reducing effects of imports and escalate the altitudes of output and economic growth.

Using sequential structural break tests, we attempt to determine if and when a new GATT member experiences statistically significant changes in the paths of its trade with incumbent members. To test for the nature of a change, we compare the averages of the actual postbreak trade shares with the averages of the postbreak extrapolated trade shares. Should a significant structural break be detected, we compare the break year with the accession year of that country to GATT. Our results show that only a small fraction of countries experience significant positive structural breaks in their trade shares. Furthermore, any significant positive breaks generally occur far before or after the time of a country's accession to GATT.

This chapter examines the empirical performance of dynamic Gaussian affine term structure models (DGATSMs) at the zero lower bound (ZLB) when principal components analysis (PCA) is used to extract factors. We begin by providing a comprehensive review of DGATSM when PCA is used to extract factors highlighting its numerous auspicious qualities; it specifies bond yields to be a simple linear function of underlying Gaussian factors. This is especially favorable since, in principle, PCA works best when the model is linear and the first two moments are sufficient to describe the data, among other characteristics. DGATSM have a strong theoretical foundation grounded in the absence of arbitrage. DGATSM produce reasonable cross-sectional fits of the yield curve. Both of these qualities are inherited into the model when PCA is used to extract the state vector. Additionally, the implementation of PCA is simple in that it takes a matter of seconds to estimate factors and is convenient to include in estimation as most software packages have ready-to-use algorithms to compute the factors immediately. The results from our empirical investigation lead us to conclude that DGATSM, when PCA is employed to extract factors, perform very poorly at the ZLB. It frequently crosses the ZLB enroot to producing negative out-of-sample forecasts for bond yields. The main implication in this study is that despite its numerous positive characteristics, DGATSM when PCA is used to extract factors produce poor empirical forecasts around the ZLB.

Densely populated South Asia faces the challenge of reducing hunger and food insecurity while combating vulnerability to climate change, natural disasters and conflicts. Home to about 36 per cent of the undernourished people in the world, the region (along with Middle East and North Africa and Sub-Saharan Africa) accounted for 84 percent of violent terrorist attacks and 95 percent of related fatalities in the world. Higher instances of temperature extremes and altered rainfall patterns accompanied with sea level rise are affecting livelihoods and pushing migration both at national and sub-national levels. In this context, the study examines conflicts (through dummies considering combinations of conflict/no conflict in the present and preceding years) and climate change (as captured by rainfall and temperature over the period 1901 to 2014) as correlates of food security using fixed-effects panel data regression analysis over the period 1991 to 2014. Our econometric findings indicate that both conflicts and climate change worsen the already precarious food security situation in South Asia. In fact, the impact is even greater when prolonged conflicts are considered. Analyzing conflict–climate interactions, food insecurity appears to further worsen with temperatures deviating from their pre-structural break averages, when considered along with prolonged armed conflicts. The study concludes by recommending policies addressing food insecurity, conflicts, and climate change adaptation and mitigation.

This paper explores the information content in the mispricing of the USD/RMB forward rates with different maturities in the deliverable forward (DF) and non-deliverable forward (NDF) markets. First, we find that the USD/RMB forward basis series are all non-stationary ones with structural breaks in both markets. This indicates the CIP does not hold in USD/RMB forward markets, either onshore or offshore. In essence, the USD/RMB forward basis is the difference of the expectation of the depreciation of the US dollar against the RMB controlled by China's Central Bank and the expected return of the US dollar as an investment asset. Second, main factors influencing the behavior of the USD/RMB forward basis are the expectation of the appreciation of the RMB controlled by China's Central Bank and the risk premium. Third, adaptive expectations play an important role in the change of the USD/RMB forward basis, particularly in NDF markets. Also the information of the NDF basis could be used to predict the spot rates in a short future. Finally, our study reveals that the risk premium of the RMB is positive for global investors in the USD/RMB NDF markets.