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Asymmetrical effects of real exchange rate on the money demand in Saudi Arabia: A non-linear ARDL approach.

ABSTRACT: This present research investigates the money demand function of Saudi Arabia using a long period 1968-2016. In addition, the asymmetrical effects of real exchange rate changes have also been explored in the estimated money demand function. Our empirical results suggest that income and inflation have positive and negative effects on money demand respectively. Further, a real appreciation of US dollar has a positive effect but a real depreciation has a negative effect on the money demand. Furthermore, income and price homogeneity hypotheses do not hold for the estimated elasticities. Moreover, the estimated model is found stable with the theoretically expected effects of money demand's determinants. Therefore, we are suggesting money supply as a monetary policy instrument to the economy of Saudi Arabia.

SUBMITTER: Mahmood H

PROVIDER: S-EPMC6261579 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Asymmetrical effects of real exchange rate on the money demand in Saudi Arabia: A non-linear ARDL approach.

Mahmood Haider H Alkhateeb Tarek Tawfik Yousef TTY

PloS one 20181128 11

This present research investigates the money demand function of Saudi Arabia using a long period 1968-2016. In addition, the asymmetrical effects of real exchange rate changes have also been explored in the estimated money demand function. Our empirical results suggest that income and inflation have positive and negative effects on money demand respectively. Further, a real appreciation of US dollar has a positive effect but a real depreciation has a negative effect on the money demand. Furtherm ...[more]

PMID: 30485329

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Project description:ObjectiveWhile macroeconomic and environmental events affect the overall economic performance of nations, there has not been much research on the effects of important macroeconomic and environmental variables and how these can influence progress. Saudi Arabia's economy relies heavily on its vast reserves of petroleum, natural gas, iron ore, gold, and copper, but its economic growth trajectory has been uneven since the 1990s. This study examines the effects of carbon emissions, rainfall, temperature, inflation, population, and unemployment on economic growth in Saudi Arabia.MethodsAnnual time series dataset covering the period 1990-2019 has been extracted from the World Bank and General Authority of Meteorology and Environmental Protection, Saudi Arabia. The Autoregressive Distributed Lag (ARDL) approach to cointegration has served to investigate the long-run relationships among the variables. Several time-series diagnostic tests have been conducted on the long-term ARDL model to check its robustness.ResultsSaudi Arabia can still achieve higher economic growth without effectively addressing its unemployment problem as both the variables are found to be highly significantly but positively cointegrated in the long-run ARDL model. While the variable of carbon emissions demonstrated a negative effect on the nation's economic growth, the variables of rainfall and temperate were to some extent cointegrated into the nation's economic growth in negative and positive ways, respectively. Like most other nations the short-run effects of inflation and population on economic growth do vary, but their long-term effects on the same are found to be positive.ConclusionsSaudi Arabia can achieve both higher economic growth and lower carbon emissions simultaneously even without effectively addressing the unemployment problem. The nation should utilize modern scientific technologies to annual rainfall losses and to reduce annual temperature in some parts of the country in order to achieve higher economic growth.

Project description:BackgroundThe characterization of reinfection with SARS-CoV-2 has been a subject of concern and controversy, especially with the surge of infections with highly transmissible variants worldwide.MethodsThis retrospective national study used comorbidities, vaccination status, SARS-CoV-2 variants of concern, and demographics data to profile participants who were reinfected with SARS-CoV-2, defined as having two reverse transcriptase-polymerase chain reaction-positive SARS-CoV-2 tests within at least 90 days apart. A multivariate logistic regression model assessed the risk factors associated with reinfection . Two control groups were selected: nonreinfected participants reporting a positive test (control group one) and those reporting a negative test (control group two).ResultsBetween March 2020 and December 2021, 4454 reinfected participants were identified in Saudi Arabia (0.8%, 95% confidence interval [CI] 0.7-0.8). The majority (67.3%) were unvaccinated (95% CI 65.9-68.7) and 0.8% (95% CI 0.6-1.1) had severe or fatal SARS-CoV-2 disease. COVID-19 vaccines were 100% effective against mortality in reinfected individuals who received at least one dose, whereas it conferred 61% (odds ratio [OR] 0.4, 95% CI 0.1-1.0) additional protection against severe disease after the first dose and 100% after the second dose. In the risk factor analysis, reinfection was highly associated with comorbidities, such as HIV (OR 2.5, 95% CI 1.3-5.2; P = 0.009), obesity (OR 2.3, 95% CI 1.3-3.9; P = 0.003), pregnancy (OR 3.2, 95% CI 1.4-7.4; P = 0.005), and working in health care facilities (OR 6.1, 95% CI 3.1-12.9; P <0.0001). The delta variant (B.1.617.2) was the most frequent variant of concern among the reinfected cohort.ConclusionThis in-depth study of the reinfection profile identified risk factors and highlighted the associated SARS-CoV-2 variants. Results showed that naturally acquired immunity to SARS-CoV-2 through multiple reinfections together with vaccine-induced immunity provided substantial protection against severe SARS-CoV-2 disease and mortality.

Project description:Diffusion exchange spectroscopy (DEXSY) provides a means to isolate the signal attenuation associated with exchange from other sources of signal loss. With the total diffusion weighting b1+b2=bs held constant, DEXSY signals acquired with b1=0 or b2=0 have no exchange weighting, while a DEXSY signal acquired with b1=b2 has maximal exchange weighting. The exchange rate can be estimated by fitting a diffusion exchange model to signals acquired with variable mixing times. Conventionally, acquired signals are normalized by a signal with b1=0 and b2=0 to remove the decay due to spin-lattice relaxation. Instead, division by a signal with equal bs but b1=0 or b2=0 reduces spin-lattice relaxation weighting of the apparent exchange rate (AXR). Furthermore, apparent diffusion-weighted R1 relaxation rates can be estimated from non-exchange-weighted DEXSY signals. Estimated R1 values are utilized to remove signal decay due to spin-lattice relaxation from exchange-weighted signals, permitting a more precise estimate of AXR with less data. Data reduction methods are proposed and tested with regards to statistical accuracy and precision of AXR estimates on simulated and experimental data. Simulations show that the methods are capable of accurately measuring the ground-truth exchange rate. The methods remain accurate even when the assumption that DEXSY signals attenuate with b is violated, as occurs for restricted diffusion. Experimental data was collected from fixed neonatal mouse spinal cord samples at 25 and 7°C using the strong static magnetic field gradient produced by a single-sided permanent magnet (i.e., an NMR MOUSE). The most rapid method for exchange measurements requires only five data points (an 80 s experiment as implemented) and achieves a similar level of accuracy and precision to the baseline method using 44 data points. This represents a significant improvement in acquisition speed, overcoming a barrier which has limited the use of DEXSY on living specimen.

Dataset Information

Asymmetrical effects of real exchange rate on the money demand in Saudi Arabia: A non-linear ARDL approach.

Publications

Asymmetrical effects of real exchange rate on the money demand in Saudi Arabia: A non-linear ARDL approach.

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