Growth path heterogeneity across provincial economies in China: the role of geography versus institutions

Liu, Guanchun; Liu, Yuanyuan

doi:10.1007/s00181-019-01639-y

Cited by 12 publications

(14 citation statements)

References 54 publications

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“…Thus, the latent classes may reflect the differences in the marginal effects of the growth factors. The finite mixture model has been applied, among others, by Owen et al [5], Di Vaio and Enflo [13], Flachaire et al [14], and Liu et al [15].…”

Section: Literature Reviewmentioning

confidence: 99%

Detecting Regimes of Economic Growth With Fuzzy Concept-Based Models

Barták

Jastrzębska

2023

IEEE Access

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The paper presents a new method to detect economic growth regimes based on time-series similarity analysis. The procedure builds upon a fuzzy concept-based model, the Jaccard Index, and a hierarchical clustering procedure. Having introduced the proposed method, we apply it to the time series of economic growth and its proximate factors. Further, we study the stability of the obtained results under different parameters. The proposed procedure allows us to detect groups of countries that share a common growth performance and akin growth mechanisms. Simultaneously, the method let us identify countries that escape any fixed classifications.INDEX TERMS Concept-based models, economic growth, growth regime, fuzzy sets.

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Section: Literature Reviewmentioning

confidence: 99%

Detecting Regimes of Economic Growth With Fuzzy Concept-Based Models

Barták

Jastrzębska

2023

IEEE Access

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“…From the theoretical viewpoint, the numbers of FDI-inequality nexus summarized in Section 2 determine the maximum of groups. From the empirical aspect, this paper not only considers the latent class marginal means, but also four kinds of information criteria (i.e., Akaike information criterion (AIC), Bayesian information criteria (BIC), corrected Akaike information criteria (CAIC) and Akaike information criteria 3 (AIC3) to ensure the correct selection of number G. 6 We calculate the possibility of being assigned in a latent group from the following multinomial logit model (Liu et al, 2020;Owen et al, 2009):…”

Section: Finite Mixture Modelmentioning

confidence: 99%

“…We calculate the possibility of being assigned in a latent group from the following multinomial logit model (Liu et al, 2020; Owen et al, 2009):

π_{a} ((),, {risk}_{q, t}, δ_{m}) = \frac{\exp ((), δ_{m} + {risk}_{q, t} δ_{m})}{\sum_{g = 1}^{G} \exp ((), δ_{g} + {risk}_{q, t} δ_{g})}

…”

Section: Empirical Strategymentioning

confidence: 99%

“…For this, we empirically reconsider FDI's impact on inequality within income distribution by utilizing country‐level panel data over the period from 1998 to 2014, which allows us to address individual heterogeneity. More importantly, this paper utilizes a data‐driven approach—that is, finite‐mixture model—in order to capture and handle unobserved heterogeneity issues as this method offers an effective way at identifying and characterizing heterogeneity (Liu, Lee, & Liu, 2020; Owen, Videras, & Davis, 2009). Concretely speaking, one major advantage of the finite‐mixture model (Fmm) is that it avoids the problem of selecting the prior threshold value to split the sample into different subcomponents, thus revealing countries in our sample are assigned into different classifications (groups) by employing Fmm, according on whether they have similar conditional distributions of income inequality 1 .…”

Section: Introductionmentioning

confidence: 99%

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Foreign direct investment, income inequality and country risk

Wang

2021

Int. J Fin Econ

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Given the continuous debate about the foreign direct investment (FDI)‐inequality nexus, there is an acknowledged need for reconsidering their relationship from a new perspective. Therefore, applying balanced panel data composed of 60 countries from 1998 to 2014, this research estimates a finite mixture model with country risk as a concomitant variable to explore the interrelationships among FDI, inequality, and country risk so as to offer fresh insight into the FDI‐inequality nexus. We present evidence that shows a significant role of compositing country risk on this. Specifically speaking, FDI deteriorates inequality under the condition of high risk, whereas it alleviates inequality in a country with low country risk. Moreover, we can also obtain the similar findings by considering the role of components of country risk (economic risk, financial risk and political risk) as a determinant for the FDI‐inequality nexus. FDI deteriorates inequality under the condition of high political, economic and financial risks, whereas it alleviates inequality in a country with low political, economic and financial risks.

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“…Third, this paper relates to the empirical literature that applies the latent class models or finite mixture models. Following Bos et al (2010) and Liu et al (2019), we permit Chinese provinces to switch regime over time, while most previous researches assume a constant growth regime for each economy (e.g., Alfo et al, 2008;Owen, et al, 2009;Flachaire et al, 2014). Fourth, this paper contributes to the empirical works using the Solow decomposition framework.…”

Section: Introductionmentioning

confidence: 99%

Growth Sources of Green Economy and Energy Consumption in China: New Evidence Accounting for Heterogeneous Regimes

Liu¹,

Liu²

2020

The Energy Journal

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This paper proposes an extended Solow decomposition framework with a finite mixture model, which is incorporated to account for heterogeneous regimes. The model decomposes green economy into two different components, namely, green total factor productivity and factor endowment. Then, we reestimate the growth sources of green economy and especially the importance of energy consumption in China’s provincial industries over 2000-2015. The empirical results suggest that there are three green growth regimes across Chinese provinces for overall economy and different industries. Specifically, some provinces switch regime over time, while the others maintain the same regime. Furthermore, when controlling for regime heterogeneity, the contribution of factor endowment decreases and that of green total factor productivity increases. With respect to energy consumption, traditional methods overestimate its importance in the primary and tertiary industries and underestimate that in the secondary industry. In addition, the reliance of China’s overall economy and the secondary and tertiary industries on energy consumption decreases as economy develops.

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Growth path heterogeneity across provincial economies in China: the role of geography versus institutions

Cited by 12 publications

References 54 publications

Detecting Regimes of Economic Growth With Fuzzy Concept-Based Models

Detecting Regimes of Economic Growth With Fuzzy Concept-Based Models

Foreign direct investment, income inequality and country risk

Growth Sources of Green Economy and Energy Consumption in China: New Evidence Accounting for Heterogeneous Regimes

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