871 resultados para cross-sectional dependence


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Este documento examina la hipótesis de sostenibilidad fiscal para 8 países de Latinoamérica. A partir de un modelo de datos panel, se determina si los ingresos y gasto primario de los Gobiernos entre 1960 - 2009 están cointegrados, es decir, si son sostenibles a largo plazo. Para esto, se utilizaron pruebas de raíz unitaria y cointegración de segunda generación con datos panel macroeconómicos, lo que permite tener en cuenta la dependencia cruzada entre los países, así como los posibles quiebres estructurales en la relación que estén determinados de manera endógena; en particular, se usan la prueba de estacionariedad de Hadri y Rao (2008) y la prueba de cointegración de Westerlund (2006). Como resultado del análisis se encontró evidencia empírica de que en el período bajo estudio el déficit primario en los 8 países latinoamericanos es sostenible pero en sentido débil.

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This paper applies stationarity tests to examine evidence of market integration for a relatively large sample of food products in Colombia. We Önd little support for market integration when using the univariate KPSS tests for stationarity. However, within a panel context and after allowing for cross sectional dependence, the Hadri tests provide much more evidence supporting the view that food markets are integrated or, in other words, that the law of one price holds for most products.

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This paper studies the impact of exogenous and endogenous shocks (exogenous shock is used interchangeably with external shock; endogenous shock is used interchangeably with domestic shock) on output fluctuations in post-communist countries during the 2000s. The first part presents the analytical framework and formulates a research hypothesis. The second part presents vector autoregressive estimation and analysis model proposed by Pesaran (2004) and Pesaran and Smith (2006) that relates bank real lending, the cyclical component of output and spreads and accounts for cross-sectional dependence (CD) across the countries. Impulse response functions show that exogenous positive shock lead to a drop in output sustainability for 9 over 12 Central Eastern European countries and Russia, when the endogenous shock is mild and ambiguous. Moreover, the effect of exogenous shock is more significant during the crises. Variance decompositions show that exogenous shock in the aftermath of crisis had a substantial impact on economic activity of emerging economies.

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Most state (and local) governments in the U.S. operate under formal fiscal rules which limit their ability to run budget deficits and resort to debt financing. A priori, one would expect to find evidence in favor of an intertemporally balanced budget, or fiscal sustainability, for these states, especially those characterized by a relatively high degree of fiscal stringency. We test this hypothesis for a panel of 47 state–local government units (1961–2006) using four budget balance definitions and several subsamples defined based on regional classifications, or presence of certain balanced budget requirements (BBRs). Our results, obtained from panel estimation techniques that allow for general forms of serial and cross-sectional dependence, suggest that a sufficient condition for “strong” sustainability is consistently satisfied for the full sample and all subsamples in relation to balances that include special funds and/or federal grants. However, we find evidence consistent with the “weak” version of sustainability for the full sample and some regional subsamples (particularly Far West dominated by California) in at least one of the two balances that exclude these items. Finally, the BBRs seem to matter only in relation to the sustainability of the more narrowly defined balances. We discuss the implications of these findings for the role of fiscal rules and federal grant policies.

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In an influential paper, Pesaran [Pesaran, M.H. (2006). Estimation and inference in large heterogeneous panels with a multifactor error structure. Econometrica 74, 967–1012] proposes a very simple estimator of factor-augmented regressions that has since then become very popular. In this note we demonstrate how the presence of correlated factor loadings can render this estimator inconsistent.

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This article investigates the impact of oil price volatility on six major emerging economies in Asia using time-series cross-section and time-series econometric techniques. To assess the robustness of the findings, we further implement such heterogeneous panel data estimation methods as Mean Group (MG), Common Correlated Effects Mean Group (CCEMG) and Augmented Mean Group (AMG) estimators to allow for cross-sectional dependence. The empirical results reveal that oil price volatility has a detrimental effect on these emerging economies. In the short run, oil price volatility influenced output growth in China and affected both GDP growth and inflation in India. In the Philippines, oil price volatility impacted on inflation, but in Indonesia, it impacted on both GDP growth and inflation before and after the Asian financial crisis. In Malaysia, oil price volatility impacted on GDP growth, although there is notably little feedback from the opposite side. For Thailand, oil price volatility influenced output growth prior to the Asian financial crisis, but the impact disappeared after the crisis. It appears that oil subsidization by the Thai Government via introduction of the oil fund played a significant role in improving the economic performance by lessening the adverse effects of oil price volatility on macroeconomic indicators.

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Using data on inequality for 21 OECD countries over the period 1870-2011 this paper tests the Piketty hypothesis that income inequality is likely to grow in the 21st century. It is shown that the null hypothesis of trend stationarity of inequality cannot be rejected at conventional significance levels, suggesting that shocks to income inequality are likely to be temporary.

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This paper proposes a simple panel data test for stock return predictability that is flexible enough to accommodate three key salient features of the data, namely, predictor persistency and endogeneity, and cross-sectional dependence. Using a large panel of Chinese stock market data comprising more than one million observations, we show that most financial and macroeconomic predictors are in fact able to predict returns. We also show how the extent of the predictability varies across industries and firm sizes.

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In this paper we examine whether order imbalances can predict the Chinese stock market returns. We use intraday data, a panel data predictive regression model that accounts for persistent and endogenous order imbalances and cross-sectional dependence in returns, and show that order imbalances predict stock returns from 1-minute trading to 90-minute trading. On the basis of this predictability evidence using multiple trading strategies we show that profits persist during the day. These results imply that a source of Chinese market inefficiency is order imbalances.

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We develop a set of nonparametric rank tests for non-stationary panels based on multivariate variance ratios which use untruncated kernels. As such, the tests do not require the choice of tuning parameters associated with bandwidth or lag length and also do not require choices with respect to numbers of common factors. The tests allow for unrestricted cross-sectional dependence and dynamic heterogeneity among the units of the panel, provided simply that a joint functional central limit theorem holds for the panel of differenced series. We provide a discussion of the relationships between our setting and the settings for which first- and second generation panel unit root tests are designed. In Monte Carlo simulations we illustrate the small-sample performance of our tests when they are used as panel unit root tests under the more restrictive DGPs for which panel unit root tests are typically designed, and for more general DGPs we also compare the small-sample performance of our nonparametric tests to parametric rank tests. Finally, we provide an empirical illustration by testing for income convergence among countries.

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This paper proposes a bootstrap test for the null hypothesis of cointegration in panel data. The test is general enough to allow for dependence both within and between the cross-sectional units, and is shown to work well in small samples. © 2007 Elsevier B.V. All rights reserved.

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One of the most cited studies in recent years within the field of nonstationary panel data analysis is that of Bai and Ng (2004), in which the authors propose PANIC, a new framework for analyzing the nonstationarity of panels with idiosyncratic and common components. The problem is that the asymptotic validity of PANIC as a platform for constructing pooled panel unit root tests based on averaging is not fully proven. This paper provides the required results, whose usefulness is verified through simulations. © 2009 Cambridge University Press.

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This paper develops a very simple test for the null hypothesis of no cointegration in panel data. The test is general enough to allow for heteroskedastic and serially correlated errors, unit-specific time trends, cross-sectional dependence and unknown structural breaks in both the intercept and slope of the cointegrated regression, which may be located at different dates for different units. The limiting distribution of the test is derived, and is found to be normal and free of nuisance parameters under the null. A small simulation study is also conducted to investigate the small-sample properties of the test. In our empirical application, we provide new evidence concerning the purchasing power parity hypothesis. © Blackwell Publishing Ltd and the Department of Economics, University of Oxford, 2008.

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In this paper, two new simple residual-based panel data tests are proposed for the null of no cointegration. The tests are simple because they do not require any correction for the temporal dependencies of the data. Yet they are able to accommodate individual specific short-run dynamics, individual specific intercept and trend terms, and individual specific slope parameters. The limiting distributions of the tests are derived and are shown to be free of nuisance parameters. The Monte Carlo results in this paper suggest that the asymptotic results are borne out well even in very small samples. Copyright © Taylor & Francis, Inc.

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This paper proposes new pooled panel unit root tests that are appropriate when the data exhibit cross-sectional dependence that is generated by a single common factor. Using sequential limit arguments, we show that the tests have a limiting normal distribution that is free of nuisance parameters and that they are unbiased against heterogenous local alternatives. Our Monte Carlo results indicate that the tests perform well in comparison to other popular tests that also presumes a common factor structure for the cross-sectional dependence.