This website uses cookies.

By clicking the "Accept" button or continuing to browse our site, you agree to first-party and session-only cookies being stored on your device to enhance site navigation and analyze site performance and traffic. For more information on our use of cookies, please see our Privacy Policy.

  1. Home
  2. ASSA Annual Meeting
  3. 2025
  4. Program
  5. Inflation, Exchange Rates, and Financial Markets Dynamics
« Back to Results

Inflation, Exchange Rates, and Financial Markets Dynamics

Paper Session

Friday, Jan. 3, 2025 8:00 AM - 10:00 AM (PST)

San Francisco Marriott Marquis, Walnut
Hosted By: Middle East Economic Association
  • Chair: Riza Demirer, Southern Illinois University Edwardsvillle

Gasoline Prices Shocks and Inflation in Lebanon: Did the 2019-2022 Gasoline Subsidies Mitigate the Effects of These Shocks?

Jana El Chaar
,
Lebanese American University
Mohamad Karaki
,
Lebanese American University

Abstract

Higher oil prices have detrimental effects on the Lebanese economy. While the manufacturing sector is relatively small (around 8 percent of GDP), oil and energy-related imports constitute around 25 percent of total imports. Since the onset of the Lebanese financial crisis in 2019, the Lebanese government has implemented a series of subsidies hoping to mitigate the inflationary pressures caused by the collapse in the value of the Lebanese pound. Economists and policymakers, however, have criticized these subsidies claiming that they cause more harm than gain. For instance, while the gasoline subsidies, kept in place until September 2022, have stabilized gasoline prices at the pump; however, such policies led to severe gasoline shortages and the emergence of a large black market.
The aim of this paper is to investigate the effect of gasoline price shocks on inflation in Lebanon before and during the Lebanese financial crisis that began in 2019. We focus on gasoline prices rather than oil prices for two reasons. First, inflation expectations tend to respond the most to salient prices such as gasoline prices (see Kilian and Zhou, 2022a, b). In fact, while a typical Lebanese household could be well aware of the prices of energy products that they observe at the pump, a few are aware of the daily global price of oil. Second, Given that gasoline products have been subsidized since the onset of the Lebanese financial crisis, then it is crucial to evaluate the transmission of energy price shocks to inflation by focusing on local gasoline prices instead of global oil products. We first estimate a linear local projection model, to assess the effect of a gasoline price shock on the overall inflation rate and the growth rate in disaggregated price indices.

The Exchange Rate-Stock Market Nexus During Normal and Extreme States and Its Economic Implications

Riza Demirer
,
Southern Illinois University Edwardsvillle

Abstract

This paper examines the extreme spillovers between stock returns and exchange rates using the quantile-on-quantile connectedness measures recently developed by Gabauer and Stenfors (2024). The novelty of this methodology is that it allows us to explore the informational spillovers between the currency and stock markets at various quantiles via the directly and reversely related spillover measures, thus offering a wider inference on the linkages between the two markets during normal and extreme up and down market states, an issue of high interest for risk management in equity and currency strategies. Using daily stock market index and exchange rate data for a group of developed and emerging economies including those in the MENA region, associated with high and low interest rate environments, we first examine the causal interactions between the stock and currency markets over time and explore the switching points that govern the lead-lag interactions between the two markets. Next, we examine the transmission of information between the two markets during normal and extreme market states characterized by various quantiles and assess the portfolio implications of the spillover effects, with a particular focus on the estimation of expected shortfall in these markets. Finally, we extend our analysis to the identification of economic and geopolitical risk factors that drive net spillovers across the two markets via mixed data sampling (MIDAS) models. By doing so, our study presents a novel perspective to the theoretical approaches that have been suggested in the literature to justify the interactions between exchange rates and stock prices with significant implications for the management of currency and stock market risks.

Financial Inclusion and Greenhouse Gases in MENA region

Freddy Rojas Cama
,
Universidad de Lima
Noha Emara
,
Rutgers University
Carolay Vasquez Quispe
,
Universidad Peruana de Ciencias Aplicadas

Abstract

This study is aimed to find an empirical linkage between financial inclusion (considering access and usage measures) and Greenhouse gases (GHG) emissions. A few years ago, most of the firms in the MENA region were not able to get loans or access to financial tools to start operations; nowadays, there is a significant effort to revert the prevalence of being financially excluded. However, financial inclusion comes with an impact of the increasing business activity on the rise of the carbon footprint. Our theoretical model discusses the energy-efficiency channel and connects the size of the firms with the high energy-consumption cost through the production process. The empirical study period covers the annual period 2004-2020 for MENA countries. We use the World Development Indicators (World Bank, 2024) to retrieve data of financial inclusion, and also additional determinants of GHG emissions such as growth of GDP per capita, foreign direct investment, renewable energy consumption, urban population and trade openness, while the data for GHG emissions are taken from Climate Data for Action (2024), and the data for globalization are taken from KOF Swiss Economic Institute (2024). Our estimation method is the Westerlund panel cointegration approach and the Cross-sectional Augmented Autoregressive Distributed Lags (CS-ARDL) model which was developed by Pesaran and Smith (1995) and Chudik and Pesaran (2015). Our results verify the confirmation of a statistical linkage at 5 and 10% of significance levels between GHG emissions, Automated teller machines (ATMs), growth of GDP per capita, foreign direct investment and globalization index in the long-term. By using the CS-ARDL, our results reveal a positive link between Automated teller machines and GHG emissions in the long run. Specifically, 1% increase in AMTs can positively increase GHG emissions in the long run by 0.326%.

On the predictability of short-run exchange rate volatility in emerging markets: Evidence from a GARCH-MIDAS Approach

Ibrahim Raheem
,
Southern Alberta Institute of Technology
Riza Demirer
,
Southern Illinois University Edwardsvillle

Abstract

This paper examines the predictive role of low frequency macroeconomic and financial indicators on the short-run exchange rate volatility in emerging markets. To do so, we develop a mixed data sampling model that forecasts short-run exchange rate volatility via the GARCH-MIDAS approach proposed by Engel et al. (2013). The GARCH-MIDAS framework has an advantage over other competing models as it can handle data of different frequencies, which makes it particularly suitable to relate high-frequency dependent variables (daily exchange rate volatility) to low-frequency independent variables (monthly financial and macroeconomic variables). In our case, our model allows the exchange rates to not only respond to market changes on a high frequency (daily) basis, but also adjust to long-run effects in response to macroeconomic and financial factors. As the selection of independent variables in exchange rate volatility models has received mixed attention, we build on Taylor-rule based fundamentals (e.g., You and Liu, 2020) and examine the predictive role of low frequency variables that capture global market conditions and uncertainty as the long-run driver of exchange rate fluctuations in emerging economies. Specifically, we consider the predictive role of geopolitical risk, economic policy uncertainty as well as the global financial cycle as the potential drivers of FX market fluctuations. By doing so, our study contributes to the recent evidence by You and Liu (2020) for developed markets in an emerging market context. Specifically, our work contributes to the literature in three aspects by (i) expanding the mixed data sampling framework to include both monetary and non-monetary fundamentals as predictors of short-run exchange rates, (ii) extending the analysis to emerging countries whose currency markets can be highly sensitive to global factors; and (iii) examining the economic implications of the exchange rate forecasts obtained from the MIDAS models.
JEL Classifications
  • G0 - General