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The purpose of this paper is to examine to what extent evidence can be found for the presence of the Marshall–Lerner (ML) condition regarding the trade balances of Egypt. The theoretical basis of the ML is presented and then tested using Egyptian trade data from 1965 to 2017.

The data are analysed via standard ordinary least squares models subject to the constraints imposed by economic theory, specifically ML theory, in which the coefficients represent elasticities. A range of tests are undertaken to establish the validity of the models and the model results including multicollinearity, unit root and co-integration in order to avoid spurious regressions.

The export model strongly suggests that real exports of Egyptian goods and services are elastic with respect to changes in the real effective exchange rate (REER), with a coefficient weight of −1.64 and is significant at 1%. However, for the import model the coefficient weight of the REER −1.17 and is significant at 1%. This result contradicts ML theory, where an increase in the REER makes imports cheaper and thus causes them to increase.

The limitations of the study are two in particular, the first is that the frequency of the data employed is annual, not monthly or even quarterly, which means that the sample size would have been larger, and the estimated parameters could have been more accurate in forecasting the future behaviour of exports and imports. There could be several other indicators that might have clear impacts on exports and imports. In other words, it is possible that a model with consumer spending and government spending as well as terms of trade, inflation, interest rate spread and taxes is going to capture more of the variation that occurs in Egypt's trade balance components.

The results suggest that the Egypt-International Monetary Fund plan (depreciation) is likely to have a positive effect on the economy. However, this does not mean that the deficit of the trade balance is going to change into a surplus once the policies of the plan are fully applied, but it does mean the deficit will reduce. Only in the long run is the trade balance likely to record a sustainable surplus. But the latter will heavily depend on the structure of exports and imports and maintaining price stability, both of which are key government policy areas.

The paper builds on previous theoretical and empirical work in this field and in particular is focussed on Egypt. There are extremely few analyses of the ML condition regarding Egypt. This paper provides new information on this and can also be utilized by researchers to further develop the analysis and method through identification of other potentially relevant variables within a single country ML study.

In continuation to Chapter 3, the present chapter tries to quantify the impact of credit upon GDP and HDI as the first attempt and the linkages of NPA and security investments with credit, GDP and HDI of the countries as the second attempt. For these purposes, this chapter starts with the measurements of credit elasticity with respect to GDP and HDI to know the impact of credit on the private sectors upon the income and human development of the countries. Then, it focuses on the implications of common banking operating tools such as their investments in the governments’ securities in relation to credit to the private sectors, GDP and HDI of the selected countries in a panel data format. The results of the credit elasticity of GDP show that it has taken the positive sign in all of the countries and the negative changes are very little in number. Furthermore, the results on the linkages show that all the variables are mostly cointegrated and therefore maintain stable and equilibrium relationships in the long run among them. But the short-run results show that investment and credit make a cause to NPA, and investment and NPA make a cause to GDP. No variables make any interrelationships with the HDI in either the long-run or short-run systems. Thus, the countries in the list should put more emphasis on the working of the financial sectors as the key partner in the income-generating activities.

This paper aims to use the newly developed panel data cointegration analysis and the dynamic time series modeling approach to examine the linkages between financial structure (market‐based vs bank‐based) and economic growth in African economies.

The research investigates the dynamic relationship between financial structure and economic growth in a panel of a group of seven African developing countries over the period of 1986‐2007. The paper uses various indicators/measures of financial structure and financial system, and employs the traditional time‐series analysis for causality as well as the newly developed panel unit root and cointegration techniques and estimated finance‐growth relationship using FMOLS for heterogeneous panel.

From the dynamic heterogeneous panel approach, the paper firstly finds that market‐based financial system is important for explaining output growth through enhancing efficiency and productivity. Second, the authors' empirical evidence supports the view that higher levels of banking system development are positively associated with capital accumulation growth and lead to faster rates of economic growth.

Panel cointegration, group mean panel FMOLS and country‐by‐country time series investigations indicate that the market‐based financial system is important for explaining output growth through enhancing efficiency and productivity, whereas the development of banking system is significantly associated with capital accumulation growth. Further results from the time‐series approach show evidence of unidirectional causality running from market‐oriented as well as bank‐oriented financial systems to economic growth.

This paper aims to identify the income and price elasticities of demand for residential electricity in Latin America and the Caribbean (LAC) and to verify their main determinants.

Meta-analysis and meta-regression methods were applied. After collecting and filtering journal articles, the authors obtained a sample composed of 76 studies covering 1979–2020.

The results show that the LAC's income elasticity is approximately 0.20 and 0.92 for the short and long term, respectively. The LAC's price elasticity is approximately −0.37 and −0.46 for the short and long term, respectively. Furthermore, the estimates are affected by the data structure, the estimation method used and the sampling period.

The authors close a gap in the literature by analyzing the price and income elasticities of demand through meta-analysis and meta-regression.

Model estimation gives students insights beyond what they can gain from textbook presentations. This paper introduces a way to make doing this easier and more effective. It introduces the program Gnu Regression, Econometrics and Time‐series Library (GRETL) which may be downloaded free of charge, and which students can place on their computers quickly and easily. Using GRETL to produce ordinary least squares (OLS) estimates is an easy, intuitive exercise. Therefore, instructors may assign such exercises without taking a large amount of time to introduce the computer and OLS estimation. GRETL, though designed to facilitate instruction, has grown into a full econometrics package that instructors can use as a research tool as well as an instructional aid.

The paper provides an overview of GRETL's accessibility and its capabilities. Next it addresses the use of GRETL for instructional purposes. Then it shows how GRETL can be used as a research tool.

The paper shows that GRETL can be a useful addition to the instructor who is showing novices how to use regression models. Also, it can be used as a research tool.

Given software like GRETL, instructors no longer need to omit model estimation because of the difficulties in accessing software and showing students how to use it.

This paper introduces a relatively new option, the use of a powerful open‐source software package to instructors in finance and accounting courses.

Construction economics scholars have emphasised the importance of construction output forecasting and have called for increased investment in infrastructure projects due to the positive relationship between construction output and economic growth. However, construction output tends to fluctuate over time. Excessive changes in the volume of construction output have a negative impact upon the construction sector, such as liquidation of construction companies and job losses. Information gleaned from extant literature suggests that fluctuation in construction output is a global problem. Evidence indicates that modelling of construction output provides information for understanding the factors responsible for these changes.

An interpretivist epistemological lens is adopted to conduct a systematic review of published studies on modelling of construction output. A thematic analysis is then presented, and the trends and gaps in current knowledge are highlighted.

It is observed that interest rate is the most common determinant of construction output. Also revealed is that very little is known about the underlying factors stimulating growth in the volume of investment in maintenance construction works. Further work is required to investigate the efficacy of using non-linear techniques for construction output modelling.

This study provides a contemporary mapping of existing knowledge relating to construction output and provides insights into gaps in current understanding that can be explored by future researchers.

Studies into ripple effects have previously focused on the interconnections between house price movements across cities over space and time. These interconnections were widely investigated in previous research using vector autoregression models. However, the effects generated from spatial information could not be captured by conventional vector autoregression models. This research aimed to incorporate spatial lags into a vector autoregression model to illustrate spatial‐temporal interconnections between house price movements across the Australian capital cities.

Geographic and demographic correlations were captured by assessing geographic distances and demographic structures between each pair of cities, respectively. Development scales of the housing market were also used to adjust spatial weights. Impulse response functions based on the estimated SpVAR model were further carried out to illustrate the ripple effects.

The results confirmed spatial correlations exist in housing price dynamics in the Australian capital cities. The spatial correlations are dependent more on the geographic rather than the demographic information.

This research investigated the spatial heterogeneity and autocorrelations of regional house prices within the context of demographic and geographic information. A spatial vector autoregression model was developed based on the demographic and geographic distance. The temporal and spatial effects on house prices in Australian capital cities were then depicted.

The volatility of exchange rate has generally been sighted as a primary cause for various shocks and instability in international trade of Ghana as witnessed over the years and most especially in recent times. Hence, owing to the increasing trade levels between Ghana and Ghana's global trading partners, the study aims to investigate if the trade–exchange rate volatility nexus in Ghana supports the positive, negative or ambiguous hypotheses?

The study investigates the effects of Ghana's exchange rate volatility on international trade by designing import and export equations to estimate both short- and long-run specifications of the effect and employing the multivariate generalized autoregressive conditional heteroskedasticity (GARCH) with Baba, Engle, Kraft and Kroner (BEKK) specification developed by Engle and Kroner (1995) as a further check for the robustness of the findings. Monthly data between 1993 and 2017 on the real effective exchange rates of Ghana's trade with 143 trading partners were taken as the series for modeling the volatility using GARCH andexponential generalized autoregressive conditional heteroskedastic (EGARCH) models.

The empirical results show that the volatility of exchange rate negatively impact export performances in the Ghanian economy. On the other hand, there was no sufficient evidence to support the observed positive effect of exchange rate volatility on imports, as the effects were only significant at 10% level in the long run. Thus, it is concluded that the finding cannot confirm a relationship between volatility and import. Thus, the results present differences in the direction of the effect of exchange rate volatility on imports and exports in the context of the Ghanaian economy.

Considering the fragility of the Ghanaian economy and Ghana's macro-economic indicators, the study points at the crucial need for more integration of well-informed trade policies within the country's macro-economic policy framework to contain the impacts of exchange rate volatility on trade performances.

The study contributes to literature by scope and method. More specifically, empirical studies have failed or provided little evidence uniquely on the Ghanaian economy's reaction to exchange rate volatility on the country's imports and exports. Additionally, most of the existing empirical studies measure exchange rate volatility using the standard deviation of the moving averages of the logarithmic transformation of exchange rates. This method is criticized because the method is unsuccessful in capturing the effects of potential booms and bursts of the exchange rate. The authors' study circumvents for these highlighted pitfalls.

The study contributes to literature by scope and method. More specifically, empirical studies have failed or provided little evidence uniquely on the Ghanaian economy's reaction to exchange rate volatility on the country's imports and exports. Thus, the study chat a course for socio-economic dynamic of Ghanaian economy.

The study contributes to literature by its scope and method, as extant empirical studies have provided little evidence specifically on the Ghanaian economy's reaction to exchange rate volatility. Additionally, most of the existing empirical studies measure exchange rate volatility using the standard deviation of the moving averages of the logarithmic transformation of exchange rates. This method is criticized because of the method's inadequacies in capturing the effects of potential booms and bursts of the exchange rate. The study thereby essentially circumvents for these highlighted pitfalls.