Ghassan Dibeh

Econometric modeling of electricity consumption in post-war Lebanon

This paper applies econometric models to investigate determinants of electrical energy consumption in post-war Lebanon. The impact of the Gross Domestic Product (GDP), proxied by total imports (TI), and degree days (DD) on electricity consumption is investigated over different time spans covering the period from 1993 to 1997. The time spans are chosen according to the rationing level of electricity supply. For the 1993–1994 time span, TI is found to be a significant determinant of energy consumption, whereas, DD has a negative correlation. This inconsistency might be attributed to an extensive rationing policy followed during this period. For the 1995–1997 time span which includes reduced rationing period (1995), all electrical energy consumption determinants are found to be significant at the 5% significance level. Analysis results for the rationing free 1996–1997 time span also show the significance of TI and DD at the 5% level. Furthermore, cointegration analysis for the 1995–1997 and 1996–1997 subsets reveals the existence of a long-run relationship between all variables. In addition, error correction models for both subsets are developed to predict short-run dynamics. Finally, statistical performance measures such as mean square error, mean average deviation and mean average percentage error are presented for all models.

An algorithm for solving bond pricing problem

The nonlinear bond pricing problem has been extensively studied in the literature. Since an analytical solution is not readily available, we will seek to find an approximate solution. We will present a decomposition method, due to Adomian, and show how to obtain a reasonable numerical solution to the bond pricing problem.

A Bayesian estimation of a stochastic predator-prey model of economic fluctuations

In this paper, we develop a Bayesian framework for the empirical estimation of the parameters of one of the best known nonlinear models of the business cycle: The Marx-inspired model of a growth cycle introduced by R. M. Goodwin. The model predicts a series of closed cycles representing the dynamics of labors share and the employment rate in the capitalist economy. The Bayesian framework is used to empirically estimate a modified Goodwin model. The original model is extended in two ways. First, we allow for exogenous periodic variations of the otherwise steady growth rates of the labor force and productivity per worker. Second, we allow for stochastic variations of those parameters. The resultant modified Goodwin model is a stochastic predator-prey model with periodic forcing. The model is then estimated using a newly developed Bayesian estimation method on data sets representing growth cycles in France and Italy during the years 1960-2005. Results show that inference of the parameters of the stochastic Goodwin model can be achieved. The comparison of the dynamics of the Goodwin model with the inferred values of parameters demonstrates quantitative agreement with the growth cycle empirical data.

Time Delays and Business Cycles: Hilferding's model revisited

This paper develops a Marxian model of the business cycle based on Hilferdings theory of disproportionality in capital accumulation in a two-sector economy. The disproportionality arises from the existence of time delays in production generated by the differential capital intensity in the two sectors. The time delays produce an asymmetric price structure that causes overproduction and crisis. The model is constructed using delay-differential equations. Numerical simulations show that the model produces an economy-wide business cycle phenomenon. The domain of the time delay parameter is investigated, and shows that the model produces a wide variety of dynamics from monotonic convergence to explosive oscillations. Moreover, the solution shows that intersectoral investment flows transmit the instability in capital accumulation and that longer time delays produce higher cycle amplitudes.

Econometric Modeling of Gasoline Consumption: A Cointegration Analysis

Abstract This article applies econometric models to investigate determinants of gasoline consumption (GC) in postwar Lebanon (1993–1999). The impact of gasoline price (P) and car registration (CR) on gasoline consumption is investigated through three models, namely, the static, autoregressive, and partial adjustment models. Analysis results showed the statistical significance of the price, at the 10% level, in affecting gasoline consumption and the insignificance of the car registration time series. Furthermore, given that regression models may produce spurious results, if time series are non-stationary, the GC, P, and CR were tested for order of integration using the Dickey-Fuller (DF) and the augmented Dickey-Fuller (ADF) tests. Cointegration analysis, using the Johansen and the Engle and Yoo test methods, revealed the existence of a long-run relationship between all variables. Moreover, an error correction model is developed to predict short-run dynamics. Finally, statistical performance measures, such as mean square error, mean average deviation, and mean average percentage error, are presented for all models.

Decomposition method for solving a nonlinear business cycle model

In this paper we present a Kaleckian-type model of a business cycle based on a nonlinear delay differential equation. A numerical algorithm based on a decomposition scheme is implemented for the approximate solution of the model. The numerical results of the underlying equation show that the business cycle is stable.

A Kaleckian model of business cycle synchronization

Abstract A non-linear, two-country Kaleckian model of the business cycle was developed for investigating business cycle synchronization. The model includes three components: a country-specific business cycle-generating equation, a transmission mechanism and time delays in the transmission mechanism. The model constructed is a non-linear delay-differential equation system. Solutions to the model without time delays in transmission are derived using the averaging method. The solutions show that the model produces limit cycles representing business cycles. The model with time delays in transmission is then solved numerically in order to investigate the role played by the coupling strength and coupling delay in transforming otherwise independent country-specific cycles into a synchronized business cycle. The degree of synchronization of the business cycle is shown to be positively related to the coupling strength. Moreover, coupling delays above a certain threshold play a desynchronizing role.

Labor market and institutional drivers of youth irregular migration in the Middle East and North Africa region

This article examines the drivers of youth irregular migration in the Middle East and North Africa region. A multinomial logit model is implemented to test the effect of labor market and institutional characteristics on the decision of youth to migrate using a unique and novel dataset covering young people aged 15–29 from five major Middle East and North Africa countries. Specifically, the article investigates the effect of micro determinants of irregular migration: individual socio-economic factors, wealth factors, adaptability factors, labor market factors, and institutional factors. The article finds that the labor market drivers matter more for regular rather than irregular migration amongst the youth from the Middle East and North Africa region. However, institutional settings are of great importance for any decision to migrate, be it regularly or irregularly. In addition, youth from wealthier households are more likely to express willingness to migrate using regular channels, whereas youth from disadvantaged backgrounds are more likely to consider the irregular route.