Question 1

11. White elephants on quicksand: Low oil prices and high geopolitical risk

Accepted Answer

We investigate the effects of low oil prices and heightened geopolitical risks on economic growth and investment in Middle East and North Africa (MENA) countries. We find that negative shocks to oil prices and positive shocks to geopolitical risk have adverse effects on GDP and investment. Moreover, we find that the impact of investment on GDP in MENA countries is muted when oil prices are low and/or geopolitical risk level is high. These findings cast doubts on the prospects of mega-project economic transformation plans as envisioned in 2030 visions for several MENA countries.
 
Full Text(https://doi.org/10.1111/sjpe.12279)

Question 2

10. The Ephemeral Brent Geopolitical Risk Premium

Accepted Answer

We study the changing relationship between Brent oil prices and geopolitical risk, conditional on physical oil market conditions. We conduct the analysis at three frequencies, medium (1-3 years), high (2-3 months), and very high (daily), using three complementary techniques at the different levels (respectively, continuous wavelet partial coherence, VAR and GARCH-MIDAS) over the period April 1993 to the end of 2018. At the annual frequency, we find evidence of a sustained positive relationship between oil prices and geopolitical risk over the past decade—with geopolitical risk leading during the Arab Spring, resulting in a substantial geopolitical risk premium, and lagging thereafter by about two months, as oil markets first reacted to and then anticipated geopolitical events. At the monthly frequency, we find the same positive correlation with oil prices anticipating geopolitical risk in both parts of the sample and find that realized geopolitical strife has not led to higher prices in either subsample. At the daily frequency, we find that geopolitical risk has had a positive effect on oil price volatility in later days during the second half of the sample (2005 to 2018). Our findings suggest that some financial market speculators, such as macro hedge funds and algorithmic traders, may amass long positions in Brent in anticipation of geopolitical threats that might potentially lead to oil disruptions.
 
Full Text(https://www.jstor.org/stable/27030660)

Question 3

9. An Optimal Early Warning System for Currency Crises under Model Uncertainty

Accepted Answer

This paper assesses several early warning (EWS) models of financial crises to propose a model that can predict the incidence of a currency crisis in developing countries. For this purpose, we employ the equal weighting (EW) and dynamic model averaging (DMA) approaches to combine forecast from individual models allowing for time-varying weights. Taking Egypt as a case study and focusing only on currency crises, our findings show that combined forecast (EW- and DMA-based EWS), to account for uncertainty, perform better than other competing models in both in-sample and out-of-sample forecasts.
 
Full Text(https://doi.org/10.1016/j.cbrev.2020.03.002)

Question 4

8. Financial liquidity, geopolitics, and oil prices

Accepted Answer

This paper aims simultaneously to study the global dynamic relationship of oil prices, financial liquidity, and geopolitical risk, on the one hand, and the economic performance of oil-exports-dependent economies on the other. Global and country-specific dynamics are studied together in a Global Vector Autoregression (GVAR) model that allows different lag structures for different variables in different countries. Global impulse response functions from the estimated model suggest that new waves of high oil prices are unlikely, despite the likely continuation of high global financial liquidity and heightened geopolitical risk, which had driven earlier episodes of very high oil prices. With oil remaining at modest to low prices by recent historical standards, we study the prospects for economic growth in oil-export-dependent economies through dramatic increases in domestic investment, as planned under Visions 2030 of some Arab countries, and conclude that, unfortunately, success is unlikely.
 
Full Text(https://doi.org/10.1016/j.eneco.2019.104482)

Question 5

7. FDI response to political shocks: What can the Arab Spring tell us?

Accepted Answer

This paper examines the FDI response to political shocks. I first investigate whether political or institutional quality is an important determinant of FDI inflows using a panel VAR model in a dataset of 146 countries over 1989–2015. Then, I exploit the Arab Spring incidence to measure the short-run effects of political shocks on FDI flows using the differences-in-differences (DiD) estimator for a sub-sample of nineteen countries in the MENA region. I account for possible bias of the DiD estimator resulting from dealing with heterogeneous group of countries by using the propensity score matching based on countries’ economic development and political settings. The findings show that a positive shock to political quality would increase FDI flows which lends evidence to the importance of political quality in determining FDI flows. In addition, I find that the Arab spring has led to a drop in FDI flows to the MENA region.
 
Full Text(https://doi.org/10.1016/j.jbef.2019.07.005)

Question 6

6. Rising inequality and de-democratization

Accepted Answer

The literature on economic determinants of democratization has identified most importantly the positive effect of economic development and the negative effect of income inequality. We confirm these results using more recent data and dynamic panel models. In this regard, the 2018 World Inequality Report has noted that inequality is highest in the Middle East, where it has stayed stable at that high level for the past several decades.
 
Full Text(https://doi.org/10.1080/17938120.2020.1720333)

Question 7

5. Arab Countries between Winter and Spring: Where Democracy Shock Goes Next!

Accepted Answer

We examine the role of democracy shocks in the cross-country economic growth processes over a period of five decades since 1960. The recent uprisings that arose independently and spread across the Arab world form the main context of our investigation. We study if (i) a shock to democracy in one country triggers institutional reforms and growth upsurge in the neighbouring countries, and (ii) the magnitude and direction of response to democracy shocks are contingent upon income pathways of countries. To estimate the spillover effects of democracy shocks, we model and estimate growth interdependence among individual countries with similar democratic characteristics. To study the nature of responses of democracy shocks on cross-country growth processes, we build and estimate a Global Vector Autoregression (GVAR) model where we allow countries to be interdependent with regard to bilateral migration and geographical proximity. Using the GVAR model, we also stimulate a positive shock to democracy in Egypt—the most populous Arabic country—and study its impacts on institutional reforms and economic growth in the rest of the Arab World. We find that high and upper-middle income countries are immune to democracy shocks in Egypt, whereas the lower middle and low income countries are susceptible to another revolutionary wave.
 
Full Text(https://doi.org/10.3390/economies7010020)

Question 8

4. Antecedents of War: The Geopolitics of Low Oil Prices and Decelerating Finanical Liquidity

Accepted Answer

We investigate the joint dynamics of oil prices, financial liquidity and geopolitical risk, within a multi-country global vector autoregressive model. We find that low oil prices are expected to trigger higher levels of geopolitical risk and that decelerating financial liquidity serves as an accelerator.
 
Full Text(https://doi.org/10.1080/13504851.2018.1494802)

Question 9

3. Asymmetric impacts of oil price shocks on government expenditures: Evidence from Saudi Arabia

Accepted Answer

This paper investigates the effect of oil price shocks on government expenditures on the health and education sectors in Saudi Arabia. Using a quarterly dataset 1990Q1–2017Q2 and employing a non-linear autoregressive distributed lag (NARDL) model, our research shows evidence of a non-linear relationship between oil prices and government expenditures in Saudi Arabia, where a negative oil price shock would have a statistically significant different impact in the long run compared to a positive shock. We build upon our empirical findings and draw some policy recommendations for Vision 2030 of Saudi Arabia.
 
Full Text(https://doi.org/10.1080/23322039.2018.1512835)

Question 10

2. Catching the mirage: The shadow impact of financial crises

Accepted Answer

This paper examines the dynamics of the shadow economy in times of financial crises. First, we estimate the size of the shadow economy in nine developing countries using energy consumption as a proxy for total economic activity. We show that our proposed proxy performs better than the conventional proxy of electricity consumption. In addition, given that financial crises usually overlap; a fact that is overlooked by existing literature, we construct a zero-one index to measure the intensity of a given shock. To explain the shadow economy impact of financial crises, we employ a set of country-specific VAR models and exploit their impulse responses. To this end, the paper finds empirical evidence of the countercyclical behaviour of the shadow economy, which suggests its buffering role in time financial crises. We show that our results are not sensitive to the method used to measure the size of the shadow economy. Finally, we build on these results to draw some policy recommendations.
 
Full Text(https://doi.org/10.1016/j.qref.2017.01.012)

Question 11

1. From Soviet to Europe: Returns to Education Puzzle in Bulgaria

Accepted Answer

This article makes a systematic presentation of returns to education in Bulgaria, a country that has witnessed a number of dramatic structural changes over the last two decades. It examines the headway of returns to education for Bulgaria in two observed economic regimes — from communism to EU membership. The findings show a steady increase in returns to education for both men and women until 2003. The average returns to one additional year of education rose from 1.1 per cent in 1986 to 5.1 per cent in 2003 for men and from 2.1 to 5.9 per cent for women. Quantile regression estimations between 1986 and 2003 evince that the most prominent increase in the wage premium occurred at the top end of the distribution, where the rate of returns to education increased in particular for women — from a negative and insignificant sign in 1986 to 7 per cent in 2003. However, this increasing trend in returns to education seems to take an inverted U-shape in 2007, the year when the country joined the EU, which poses a new puzzle to be resolved. To this end, the current article introduces possible explanations for such a puzzle and sheds lights on a number of insightful policy implications.
 
Full Text(https://doi.org/10.1111/labr.12080)

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