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1 – 10 of 35Asif Tariq, Masroor Ahmad and Aadil Amin
Standard economic theory predicts that any increase in public spending is accompanied by a rise in inflation in an economy. This paper presents empirical proof that prices do not…
Abstract
Purpose
Standard economic theory predicts that any increase in public spending is accompanied by a rise in inflation in an economy. This paper presents empirical proof that prices do not always rise with an increase in public expenditure but only up to a certain threshold level. The primary aim of this paper is to unearth the government size-inflation nexus in India for the period from 1971 to 2019.
Design/methodology/approach
The logistic STAR (smooth transition autoregression) model is employed to unravel the government size-inflation nexus for the Indian economy from a non-linear perspective.
Findings
The finding of our study confirm the non-linear relationship between the size of the government and inflation in India. The estimated threshold level for government size is precisely found to be 9.27%. The size of the government exerts a negative influence on inflation until it reaches the optimal or threshold level. Any further increase in the size of government beyond this threshold level would result in a rise in inflation.
Research limitations/implications
The findings have implications for the conduct of fiscal policy. Policymakers can increase government spending in a regime of small government size without having any inflationary impacts by generating revenues from taxes and other sources instead of relying much on the central bank. In the regime of a large-sized government, adhering strictly to the discipline in the conduct of fiscal and monetary policies would help curb inflation and enhance growth synchronously, hence alleviating any loss of welfare.
Originality/value
To the best of the authors’ knowledge, this study is an attempt to revisit the government size-inflation nexus in India from a non-linear perspective using the Smooth Transition Autoregression (STAR) model for the first time.
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Anam Ul Haq Ganie and Masroor Ahmad
The purpose of this study is to investigate the nonlinear effects of renewable energy (RE) consumption and economic growth on per capita CO2 emissions during the time span from…
Abstract
Purpose
The purpose of this study is to investigate the nonlinear effects of renewable energy (RE) consumption and economic growth on per capita CO2 emissions during the time span from 1980 to 2020.
Design/methodology/approach
The study uses the logistic smooth transition autoregression (STAR) model to decipher the nonlinear relationship between RE consumption, economic growth and CO2 emissions in the Indian economy.
Findings
The estimated results confirm a nonlinear relationship between India’s economic growth, RE consumption and CO2 emissions. The authors found that economic growth positively impacts CO2 emissions until it reaches a specific threshold of 1.81 (per capita growth). Beyond this point, further economic growth leads to a reduction in CO2 emissions. Similarly, RE consumption positively affects CO2 emissions until economic growth reaches the same threshold level, after which an increase in RE consumption negatively impacts CO2 emissions.
Research limitations/implications
The study suggests that India should optimize the balance between economic growth and RE consumption to mitigate CO2 emissions. Policymakers should prioritize the adoption of RE during the early stages of economic growth. As economic growth reaches the specific threshold of 1.81 per capita, the economy should shift to more sustainable and energy-efficient practices to limit the effect of further CO2 emissions on further economic growth.
Originality/value
To the best of the authors’ knowledge, this study represents the first-ever endeavor to reexamine the nonlinear relationship between RE consumption, economic growth and CO2 emissions in India, using the STAR model.
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Kirstin Hubrich and Timo Teräsvirta
This survey focuses on two families of nonlinear vector time series models, the family of vector threshold regression (VTR) models and that of vector smooth transition regression…
Abstract
This survey focuses on two families of nonlinear vector time series models, the family of vector threshold regression (VTR) models and that of vector smooth transition regression (VSTR) models. These two model classes contain incomplete models in the sense that strongly exogeneous variables are allowed in the equations. The emphasis is on stationary models, but the considerations also include nonstationary VTR and VSTR models with cointegrated variables. Model specification, estimation and evaluation is considered, and the use of the models illustrated by macroeconomic examples from the literature.
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Salima Ben Ezzeddine and Kamel Naoui
The aim of this chapter is to assess the real exchange rate misalignments. A smooth transition autoregressive model (STAR) is used for Tunisian exchange market. This model allows…
Abstract
The aim of this chapter is to assess the real exchange rate misalignments. A smooth transition autoregressive model (STAR) is used for Tunisian exchange market. This model allows us to see whether these differences are temporary or persistent over the period 1975–2012. We start by defining the exchange rate’s fundamental determinants to provide the equilibrium exchange rate value. Then, we study the observed exchange rate adjustment toward its equilibrium level. Vector autoregressive model and vector error correction model are applied to characterize the joint dynamics of variables in the long run. The results indicate a long-run relationship between variables. In order to consider the nonlinearity for better results, we will move to nonlinear smooth transition model. We found there is a high degree of exchange rate misalignment. We recognized that this difference decreases in the long run and disappears at the end.
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Hedibert Freitas Lopes and Esther Salazar
In this paper, we propose a Bayesian approach to model the level and the variance of (financial) time series by the special class of nonlinear time series models known as the…
Abstract
In this paper, we propose a Bayesian approach to model the level and the variance of (financial) time series by the special class of nonlinear time series models known as the logistic smooth transition autoregressive models, or simply the LSTAR models. We first propose a Markov Chain Monte Carlo (MCMC) algorithm for the levels of the time series and then adapt it to model the stochastic volatilities. The LSTAR order is selected by three information criteria: the well-known AIC and BIC, and by the deviance information criteria, or DIC. We apply our algorithm to a synthetic data and two real time series, namely the canadian lynx data and the SP500 returns.
Marianna Oliskevych and Iryna Lukianenko
The purpose of this paper is to investigate the behavior peculiarities of the labor force participation in Eastern European countries.
Abstract
Purpose
The purpose of this paper is to investigate the behavior peculiarities of the labor force participation in Eastern European countries.
Design/methodology/approach
The authors provide the analysis of nonlinearity in dynamics of economic active population and perform the econometric analysis using logistic smooth transition autoregressive models that are flexible and capture various kinds of behavior for different modes. The paper investigates labor markets of six Eastern European countries, Hungary, Bulgaria, Poland, Slovakia, Romania and Croatia that are characterized by lower level of labor force participation rate (LFPR) than average level in EU.
Findings
The results of modeling quantitatively characterize smooth changes in the behavior modes of labor force activity for each country and indicate how population economic activity depends on previous labor market states. The estimated slope parameters that determine the smoothness of transition between regimes show that, in all countries, the labor force participation quite quickly reacts to changes that occurred on the labor market in the past. During recession periods, households of European countries that joint EU last decade in order to prevent the depletion of their total income increased labor supply and showed increased activity in job search.
Originality/value
This paper indicates the nonlinearity and asymmetry in LFPR in transition economies, discovers variety of its dynamics in the different regimes and determines the indicators that cause the change of the population economic activity behavior in each country.
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I survey applications of Markov switching models to the asset pricing and portfolio choice literatures. In particular, I discuss the potential that Markov switching models have to…
Abstract
I survey applications of Markov switching models to the asset pricing and portfolio choice literatures. In particular, I discuss the potential that Markov switching models have to fit financial time series and at the same time provide powerful tools to test hypotheses formulated in the light of financial theories, and to generate positive economic value, as measured by risk-adjusted performances, in dynamic asset allocation applications. The chapter also reviews the role of Markov switching dynamics in modern asset pricing models in which the no-arbitrage principle is used to characterize the properties of the fundamental pricing measure in the presence of regimes.
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Gustavo Barboza, Laura Gavinelli, Valerien Pede, Alice Mazzucchelli and Angelo Di Gregorio
The purpose is to detect the nonlinearity wholesale rice price formation process in Italy in the 1995–2017 period.
Abstract
Purpose
The purpose is to detect the nonlinearity wholesale rice price formation process in Italy in the 1995–2017 period.
Design/methodology/approach
A nonlinear smooth transition autoregressive (STAR)-type dynamics model is used.
Findings
Wholesale rice prices are significantly affected by variations in the international price of rice as well as variations in Arborio price.
Research limitations/implications
The limitations include policy recommendations for the production and commercialization of rice in Italy.
Practical implications
Understanding rice pricing dynamics and nonlinearity behavior is pivotal for the survival of the entire European and Italian rice supply chain.
Originality/value
In the extant literature, no evidence exists on non-linearity of rice prices in Italy.
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