nep-ets New Economics Papers
on Econometric Time Series
Issue of 2021‒05‒31
six papers chosen by
Jaqueson K. Galimberti
Auckland University of Technology

  1. Specification tests for GARCH processes By Giuseppe Cavaliere; Indeewara Perera; Anders Rahbek
  2. Vector autoregression models with skewness and heavy tails By Karlsson, Sune; Mazur, Stepan; Nguyen, Hoang
  4. Comparison of Local Projection Estimators for Proxy Vector Autoregressions By Martin Bruns; Helmut Lütkepohl
  5. A new test for common breaks in heterogeneous panel data models By Jiang, Peiyun; Kurozumi, Eiji
  6. GDP Modelling and Forecasting Using ARIMA. An Empirical Assessment for Innovative Economy Formation By VINTU, Denis

  1. By: Giuseppe Cavaliere (Department of Economics, Exeter Business School, Department of Economics, University of Bologna,); Indeewara Perera (Department of Economics, The University of Sheffield); Anders Rahbek (Department of Economics, University of Copenhagen)
    Abstract: This paper develops tests for the correct specification of the conditional variance function in GARCH models when the true parameter may lie on the boundary of the parameter space. The test statistics considered are of Kolmogorov-Smirnov and Cramér-von Mises type, and are based on a certain empirical process marked by centered squared residuals. The limiting distributions of the test statistics are not free from (unknown) nuisance parameters, and hence critical values cannot be tabulated. A novel bootstrap procedure is proposed to implement the tests; it is shown to be asymptotically valid under general conditions, irrespective of the presence of nuisance parameters on the boundary. The proposed bootstrap approach is based on shrinking of the parameter estimates used to generate the bootstrap sample toward the boundary of the parameter space at a proper rate. It is simple to implement and fast in applications, as the associated test statistics have simple closed form expressions. A simulation study demonstrates that the new tests: (i) have excellent finite sample behaviour in terms of empirical rejection probabilities under the null as well as under the alternative; (ii) provide a useful complement to existing procedures based on Ljung-Box type approaches. Two data examples are considered to illustrate the tests.
    Keywords: GARCH model, bootstrap, specification test, Kolmogorov-Smirnov test, Cramér-von Mises test, marked empirical process, nuisance parameters on the boundary,
    Date: 2021–05–25
  2. By: Karlsson, Sune (Örebro University School of Business); Mazur, Stepan (Örebro University School of Business); Nguyen, Hoang (Örebro University School of Business)
    Abstract: With uncertain changes of the economic environment, macroeconomic downturns during recessions and crises can hardly be explained by a Gaussian structural shock. There is evidence that the distribution of macroeconomic variables is skewed and heavy tailed. In this paper, we contribute to the literature by extending a vector autore- gression (VAR) model to account for a more realistic assumption of the multivariate distribution of the macroeconomic variables. We propose a general class of generalized hyperbolic skew Student's t distribution with stochastic volatility for the error term in the VAR model that allows us to take into account skewness and heavy tails. Tools for Bayesian inference and model selection using a Gibbs sampler are provided. In an empirical study, we present evidence of skewness and heavy tails for monthly macroe- conomic variables. The analysis also gives a clear message that skewness should be taken into account for better predictions during recessions and crises.
    Keywords: Vector autoregression; Skewness and heavy tails; Generalized hyper- bolic skew Students t distribution; Stochastic volatility; Markov Chain Monte Carlo
    JEL: C11 C15 C16 C32 C52
    Date: 2021–05–20
  3. By: Sandoval Paucar, Giovanny
    Abstract: The article investigates the uncertainty and interdependence between the Colombian stock market and the main international markets. A Dynamic Conditional Correlation Model (DCC) is estimated to study the interdependence between selected stock markets and a GARCH model to analyze conditional volatility. To this end, a daily data sample is used, covering the period between January, 2001 and September, 2018. The results show that the subprime crisis period generates a significant positive effect on the conditional volatility. In addition, there is a significant co-movement in time between the Colombian stock market and national and international markets. Finally, I find evidence of financial contagion in periods of the subprime crisis and European debt
    Keywords: Dynamic conditional correlation, financial crises, multivariate GARCH, financial markets, interdependence
    JEL: C15 F32 F36 G15
    Date: 2021–05–25
  4. By: Martin Bruns (University of East Anglia); Helmut Lütkepohl (DIW Berlin and The Free University of Berlin)
    Abstract: Different local projection (LP) estimators for structural impulse responses of proxy vector autoregressions are reviewed and compared algebraically and with respect to their small sample suitability for inference. Conditions for numerical equivalence and similarities of some estimators are provided. A new LP type estimator is also proposed which is very easy to compute. Two generalized least squares (GLS) projection estimators are found to be more accurate than the other LP estimators in small samples. In particular, a lag-augmented GLS estimator tends to be superior to its competitors and to perform as well as a standard VAR estimator for sufficiently large samples.
    Keywords: Structural vector autoregression, local projection, impulse responses, instrumental variable
    JEL: C32
    Date: 2021–05–28
  5. By: Jiang, Peiyun; Kurozumi, Eiji
    Abstract: In this paper, we develop a new test to detect whether break points are common in heterogeneous panel data models where the time series dimension T could be large relative to cross-section dimension N. The error process is assumed to be cross-sectionally independent. The test is based on the cumulative sum (CUSUM) of ordinary least squares (OLS) residuals. We derive the asymptotic distribution of the detecting statistic under the null hypothesis, while proving the consistency of the test under the alternative. Monte Carlo simulations and an empirical example show good performance of the test.
    Keywords: CUSUM test, panel data, structural change, common breaks
    JEL: C12 C23
    Date: 2021–05
  6. By: VINTU, Denis
    Abstract: This article reconsiders the developing of a new forecast model using the interrupted timeseries of the gross domestic product for the Republic of Moldova. The theme arises from a first need to redefine, economic growth in the context of increasing globalization but also the complexity of commercial transactions. The forecasting method used is based on ARIMA each model partly emphasizing the urgent need to redefine, the economic growth in the context of the Association Agreement (AA) with the EU, which includes a Comprehensive Free Trade Agreement (2014) but also future prospects of integration among the countries with an average degree of development. The technique used comes to bring novelty in the field of forecasting, as an alternative to the one which should be —, a simultaneous equations method and traditional VAR. The policy and practical implications of the results are the strengths. The limits are due to the high degree of risk and uncertainty, which is due to the low degree of real convergence of the economy, but also to other factors such as the regional context, the lack of openness of the economy, the diversification of exports and services. The degree of complexity arises from the adaptation and study of the chronological interrupted series 1967−2019 for the branch – information and communications, subgroup GDP, categories of resources, which themselves have specific asymmetries and nuances. The basic ARIMA equations are generally used in conjunction with three sets of assumptions regarding the formation of the gross domestic product, referring to the elasticity of aggregate demand or excess sensitivity supply in the goods and labour markets. Another hypothesis concerns the rigid wage and sticky prices, including deflation with an positive output gap only in the telecom market. Also, the salary is rigid, while the price level is adjusted based on the market of goods and commodities, so that the excess supply appears only in the labour market. Finally, in a third assumption, both markets are assumed to be mutually adjusted. The multipliers of fiscal and monetary policy, besides the conclusions that can be drawn about economic policy, are obviously different in these three assumptions. The article presents a synthetic model that supports the three particular sub-regimes of assumptions of a single adapted ARIMA model, namely the trajectory of New Keynesian Small and Closed Economy Model – a balance in the goods and services, the labour market and the national financial system. In conclusion, the model aims not only to redefine the area of macroeconomic forecasting but also to offer a future perspective of adopting combined techniques such as the Stochastic Dynamic General Equilibrium (K-SDGE) Model with sticky prices and wages – technique, but also the scenario method. This framework is appealing because it has straight forward model setup, transparent mechanisms, sharp empirical analysis, and multiple important applications such as rational expectations.
    Keywords: economic growth and aggregate productivity, the gross domestic product, innovation and communications, cross-country output convergence, prediction and forecasting methods,time series analysis and modelling, ARIMA modelling, Box-Jenkins method.
    JEL: C12 C14 C22 C53 D62 D84 F15 F21 F61 O10 O30
    Date: 2021–04–23

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