Investment and saving in Angola and the Feldstein–Horioka puzzle

Barros, Carlos Pestana; Gil-Alana, Luís A.

doi:10.1080/00036846.2015.1034844

Cited by 10 publications

(3 citation statements)

References 31 publications

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“…It is noteworthy to observe that some attempts in testing the Feldstein–Horioka hypothesis for African countries have been made in the last decade and a half. Some important empirical investigations in this regard are, the studies conducted by Cooray and Sinha (2007), De Wet and Van Eyden (2005), Murthy (2005), Adedeji and Thornton (2007), Cyrille (2010), Bangake and Eggoh (2011, 2012), Kumar, Sen, and Srivastava (2014), Barros and Gil‐Alana (2015), Gil‐Alana, Andre, Gupta, Chang, and Ranjbar (2016), Raheem (2017). Adedeji and Thornton (2007) employed FMOLS and DOLS estimators allowing for heterogeneity and cross‐sectional dependence effects.…”

Section: Literature Surveymentioning

confidence: 99%

The Feldstein–Horioka hypothesis for African countries: Evidence from recent panel error‐correction modelling

Murthy

Ketenci

2020

Int. J Fin Econ

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This paper, by applying the recent panel data error‐correction modelling developed by Gengenbach et al., Panel error correction testing with global stochastic trends, 2008 University of Maastricht, Working Paper, RM/08/051:1–51 and Gengenbach et al., Journal of Applied Econometrics, 2016, 31, 982–1004 tests the validity of the Feldstein–Horioka puzzle (1980) in a panel of 27 African countries for the period 1965–2015. Unlike the existing studies in the literature, this paper, for the first time, addresses several important panel data econometric issues such as slope heterogeneity, cross‐section dependence, unobservable common factors, non‐stationarity and endogeneity that would yield inconsistent and biased estimates of the parameters of interest. Unlike the previous residual‐based error‐correction modelling that has low power, the Gengenbach et al., Panel error correction testing with global stochastic trends, 2008, University of Maastricht, Working Paper, RM/08/051:1–51 and Gengenbach et al., Journal of Applied Econometrics, 2016, 31, 982–1004 estimator explicitly considers structural dynamics in modelling a cointegrated panel that allows for the presence of non‐stationary unobserved common factors. As the GUW modelling depends on the Pesaran Common Correlated Effects Mean Group Estimator (CCEMG; 2006) and the Chudik and Pesaran Dynamic Common Correlated Effects Mean Group Estimator (DCCEMG; 2015), we report the results based on these estimators. The econometric exercises performed in the paper show that slope heterogeneity; cross‐section dependence and non‐stationarity are present in the panel data sample used in the estimation. Estimations yield a relatively low magnitude of the savings retention coefficient for the panel members included in the study with a negative error‐correction term that is statistically significant at the individual and panel levels. The empirical evidence rejects the presence of the Feldstein–Horioka puzzle in the panel of 27 African countries studied.

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Section: Literature Surveymentioning

confidence: 99%

The Feldstein–Horioka hypothesis for African countries: Evidence from recent panel error‐correction modelling

Murthy

Ketenci

2020

Int. J Fin Econ

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“…The contrary version of the time series data approach includes the discussion offered by Barros and Gil‐Alana (2015), Corbin (2004), and Hoffmann (2004). This school of thought found no or low long‐run affiliation between the domestic savings and investment ratio implying significant international mobility of capital.…”

Section: Theoretical Framework On the Urbanization Globalization And Fdimentioning

confidence: 99%

New insight into Feldstein and Horioka Paradox: Analyzing the mediating roles of globalization, urbanization, and foreign direct investment

Akadırı¹,

Apinran²,

Usman³

2020

J Public Affairs

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Different dimensions abound to examine the famous Feldstein–Horioka Puzzle. However, after intense discussions of the subject matter for more than three decades, researchers are yet to reach consensus on the validity or otherwise of savings–investment relationship. In this paper, we revisited the Feldstein–Horioka saving‐investment puzzle, and augment their investment equation with factors that drive capital mobility, such as globalization, foreign direct investment, and urbanization using more recent annual frequency time series data over the periods 1981–2018 in the case of Nigeria. We employed unit root test with structural breaks/regime shifts inherent in time series data and Autoregressive Distributed Lag Bounds Testing for co‐integration of empirical estimates. Results show existence of a long‐run equilibrium relationship among variables. Domestic savings, real income, and foreign direct investment reveal positive impact, while globalization and urbanization exhibit negative impact on domestic investment both in the short and long run. We find strong capital mobility among savings–investment relationship, thus render potential policy suggestions that would drive domestic investment and bring about sustainable economic growth in the long run.

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“…Many of them show that the statistical significance between domestic saving and investment is prevailing and thereby reflect a long-run linkage by validating the arguments of Feldstein and Horioka (1980) in which the degree of international capital mobility is low (Jansen, 1996;Narayan, 2005aNarayan, , 2005bCaporale et al, 2005). However, some other discussions developed by Barros and Gil-Alana (2015) and Ma and Li (2016) support the fact that those empirical findings do not support the long-run estimates of saving-investment nexus that implies the presence of a high degree of financial integration, where the saving-retention coefficient is low enough. Finally, the last strand of studies uses the panel data approach for several reasons such as providing of more accurate inference of model parameters, having a great capacity for capturing the complexity of the sample, having more control for the impact of omitted variables, having power to uncover dynamic linkages, generating more accurate predictions for individual outcomes through the pooling of data, and simplifying power of the statistical inferences (de Wet and van Eyden, 2005;Guillaumin, 2009;Bangake and Eggoh, 2011;Mosikari et al, 2017).…”

Section: Introductionmentioning

confidence: 95%

The Relevance of Financial Integration Across Europe: A Dynamic Panel Data Approach

Özdemir¹,

Kayhan²

2021

R. Econ. and Finan.

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This paper aims to examine the degree of financial integration for selected European countries from 1980 to 2019 using dynamic panel data approaches, covering the panel unit-root tests, cointegration analysis, panel Granger causality tests, and the DOLS and FMOLS methods. Saving and investment rates are found to be stationary at order of integration one, i.e., I (1). It is also found to be that the series are cointegrated along with different methods. Similar to that of cointegration analysis, it is observed that the causality between the variables is statistically significant and bidirectional. Finally, the current study proceeds to test the direction of coefficients for the estimation of the long-run relationship among the series by way of using panel DOLS and FMOLS methods. The values of coefficients show that the effects of each variable on another are both positive and statistically significant at the 1% level. Therefore, the empirical findings point out that strong financial integration is relevant to those European countries.

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Investment and saving in Angola and the Feldstein–Horioka puzzle

Cited by 10 publications

References 31 publications

The Feldstein–Horioka hypothesis for African countries: Evidence from recent panel error‐correction modelling

The Feldstein–Horioka hypothesis for African countries: Evidence from recent panel error‐correction modelling

New insight into Feldstein and Horioka Paradox: Analyzing the mediating roles of globalization, urbanization, and foreign direct investment

The Relevance of Financial Integration Across Europe: A Dynamic Panel Data Approach

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