Hypothesizing directional causality between the governance indicators and economic growth: the case of Afghanistan

Abstract

This paper examines the causal relationship between governance indicators and economic growth in Afghanistan. We use a set of quarterly time series data from 2003Q1 to 2018Q4 to test our hypothesis. Following Toda and Yamamoto’s (J Econom 66(1–2):225–250, 1995. 10.1016/0304-4076(94)01616-8) vector autoregressive model and the modified Wald test, our empirical results show a unidirectional causality between the government effectiveness, rule of law, and the economic growth. Our findings exhibit significant causal relationships running from economic growth to the eradication of corruption, the establishment of the rule of law, quality of regulatory measures, government effectiveness, and political stability. More interestingly, we support the significant multidimensional causality hypothesis among the governance indicators. Overall, our findings not only reveal causality between economic growth and governance indicators, but they also show interdependencies among the governance indicators.

The health consequences of civil wars: evidence from Afghanistan

“…Assuming that the variables follow a mixed order of integration and if we let the maximum integration to be , then in our case, . In such circumstances, common cointegration methods do not provide consistent results, while in Johansen’s [ 61 – 63 ] cointegration method, any I(2) series is defined as a sub-model of the basic vector autoregressive (VAR) model through two reduced rank conditions [ 64 ] using the matrix comprising trace-statistics and max-eigenvalues to establish a long-run nexus between the predictors, accounting for any I(2) series in a sample of variables [ 61 ]. The optimal lag length both for unit root and Johansen’s cointegration equations are selected using the AIC (Akaike Information Criterion), SIC (Schwarz Information Criterion), and HQIC (Hanan-Quinn Information Criterion) in the unrestricted VAR model.…”

“…Instructed by the unit root results (see Table 3 ) by having mixed integrating order with maximum series and based on an extensive empirical literature (see, for instance, [ 61 , 62 ]), the study employs the Toda and Yamamoto’s [ 65 ] modified VAR model, which is an appropriate estimation method for the case of this study. The modification is built upon the augmented VAR model—that is, the augmented with the optimal lags selected via information criteria plus allowing for lags to the number of variables plugged into the unrestricted VAR model expressed as: …”

Assessing the asymmetric war-growth nexus: A case of Afghanistan

“…First, it allows the predictors to follow mixed integrating orders. Second, it provides consistent and accurate results even in small samples [ 62 ]. Third, it allows the dependent and independent variables to augment different lags in computation.…”

Influence of Governance Components on Economic Growth in Tanzania

“…The study discovered that, with the exception of regulatory quality, all governance metrics had a statistically significant beneficial influence on economic growth. Shafiq and Azimi (2020) explored the association between governance variables and Afghan economic growth. Their empirical findings demonstrated a one-way relationship between the rule of law, government effectiveness, and economic growth.…”

“…The private sector's massive financial resources and knowledge in market-based results have the latent for undertaking systemic societal tests (Dimoso & Andrew, 2021;Kitole et al, 2023). Presently employing around 70 percent of the youth in Tanzania, the private sector delivers a critical way to selfreliance (Clyde, 2020;Azimi, 2020) On 7 September 2021, the IMF agreed USD 567.25 million in backup financial aid to support Tanzania's efforts in retorting to the Covid-19 pandemic by handling the pressing health, economic and humanitarian costs. The IMF forecasts a GDP growth for Tanzania between +4.0% and +5.1% in 2021 and 2022 respectively, and 6.0% in 2026.…”