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In this chapter we approach the estimation of dynamic stochastic general equilibrium models through a moments-based estimator, the empirical likelihood. We attempt to show that this inference process can be a valid alternative to maximum likelihood, which has been one of the preferred choices of the related literature to estimate these models. The empirical likelihood estimator is characterized by a simple setup and only requires knowledge about the moments of the data generating process of the model. In this context, we exploit the fact that these economies can be formulated as a set of moment conditions to infer on their parameters through this technique. For illustrational purposes, we consider a standard real business cycle model with a constant relative risk averse utility function and indivisible labor, driven by a normal technology shock.

This paper gives a selective review on some recent developments of nonparametric methods in both continuous and discrete time finance, particularly in the areas of nonparametric estimation and testing of diffusion processes, nonparametric testing of parametric diffusion models, nonparametric pricing of derivatives, nonparametric estimation and hypothesis testing for nonlinear pricing kernel, and nonparametric predictability of asset returns. For each financial context, the paper discusses the suitable statistical concepts, models, and modeling procedures, as well as some of their applications to financial data. Their relative strengths and weaknesses are discussed. Much theoretical and empirical research is needed in this area, and more importantly, the paper points to several aspects that deserve further investigation.

This paper analyzes the impact of economic downturns on the revenue and expense sides of city financing for the period 2003 to 2009 using a convenience sample of the audited end of year financial reports for thirty midsized US cities. The analysis focuses on whether and how quickly and how extensively revenue and spending directions from past years are altered by recessions. A seven year series of Comprehensive Annual Financial Report (CAFR) data serves to explore whether citiesʼ revenues and spending, especially the traditional property tax and core functions such as public safety and infrastructure withstood the brief 2001 and the persistent 2007 recessions? The findings point to consumption (spending) over stability (revenue minus expense) for the recession of 2007, particularly in 2008 and 2009.

The purpose of this paper is to investigate the influence of macroeconomic cyclical indicators and country governance on bank non-performing loans in African countries.

Data was collected from the 53 African countries covering 2005–2021. The paper develops an empirical model to examine the impact of country governance in reducing macroeconomic cycle-induced adverse effects on bank credit risk. This research estimates Random Effects models and the General Method of Moment to examine the link between microeconomic and governance factors on bank non-performing loans. Stata version 15.1 was used to conduct panel regression analysis.

The findings of the study revealed that the generalized method of moments findings contributes valuable insights into the persistence of NPLs over time and the specific effects of variables on NPL levels. The study findings highlight that the debt-to-GDP ratio, unemployment, regulatory quality, government effectiveness and inflation have significant relationships with NPLs, shedding light on their specific contributions to credit risk dynamics.

The focus on a specific set of determinants for NPLs, which may not capture all the factors that influence NPL levels. Thus, the study did not consider the impact of macroeconomic shocks, such as natural disasters or global economic crises, which can have a significant impact on NPLs.

Policymakers should prioritize maintaining sustainable debt levels, promoting employment growth and controlling inflation rates to mitigate credit risk and reduce nonperforming loans. Also, enhancing regulatory quality and government effectiveness is crucial in ensuring financial stability and minimizing non-performing loans in Africa.

This paper provides a new possible solution to minimise bank non-performing loans risk by examining interactions of country governance regarding the macroeconomic cycle behaviour.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-11-2022-0729

This paper seeks to reconsider the Euler equation of the Consumption Capital Asset Pricing Model (CCAPM), to derive a regression‐based model to test it, and to present evidence that the model is consistent with reasonable values for the coefficient of relative risk aversion (CRRA). This runs contrary to the findings of the literature on the equity premium puzzle, but is in agreement with the literature that estimates the CRRA for the purpose of computing the social discount rate, and is in line with the research on labor supply. Tests based on General Method of Moments (GMM) for the same sample produce results that are extremely disparate and unstable. The paper aims to check and find support for the robustness of the regression‐based tests. Habit formation models are also to be evaluated with regression‐based and GMM tests. However, the validity of the regression‐based models depends critically on their functional forms.

The paper presents empirical evidence that the conventional use of GMM fails because of four pathological features of GMM that are referred to under the general caption of “weak identification”. In addition to GMM, the paper employs linear regression analysis to test the CCAPM, and it is found that the regression residuals follow well‐behaved distributional properties, making valid all statistical inferences, while GMM estimates are highly unstable.

Four unexpected findings are reported. The first is that the regression‐based models are consistent with reasonable values for the CRRA, i.e. estimates that are below 4. The second is that the regression‐based tests are robust, while the GMM‐based tests are not. The third is that regression‐based tests with habit formation depend crucially on the specification of the model. The fourth is that there is evidence that market stock returns are sensitive to both consumption and dividends. The author calls the latter “extra sensitivity of market stock returns”, and it is described as a new puzzle.

The regression‐based models of the CCAPM Euler equation are novel. The comparison between GMM and regression‐based models for the same sample is original. The regression‐based models with habit formation are new. The equity premium puzzle disappears because the estimates of the CRRA are reasonable. But another puzzle is documented, which is the “extra sensitivity of market stock returns” to consumption and dividends together.

This study examines the asymmetric effect of government spending on economic growth in Nigeria over the period 1980–2017. Specifically, this study investigates whether the response of economic growth to government spending shocks differs according to the nature of shocks on them. In addition, the authors examine whether the stabilizing effects of fiscal policies are dependent on the state of the business cycle.

The study adopts the linear fiscal reaction function in addition to the nonlinear regression model of Hatemi-J (2011, 2012), Granger and Yoon (2002), which allows us to separate negative shocks from positive shocks to government spending. Similarly, the authors adopt the generalized method of moments (GMM) techniques of Hansen (1982) to account for simultaneity and endogeneity problems inherent in dynamic model.

The authors’ findings reveal that there is evidence of asymmetry in the government spending–economic growth nexus in Nigeria over the period of study. Specifically, the authors find that the response of economic growth to government spending shocks differs according to the nature of shocks on them. More specifically, the study established that the stabilizing effects of fiscal policies are dependent on the state of the business cycle.

Unlike the traditional method of modeling asymmetry, which adopts the simple inclusion of a squared government spending term or by the inclusion of a cubic government spending term, the model adopted in this study allows us to model shocks and show how the responses of economic growth to government expenditure differ according to the nature of shocks on them.

The purpose of this paper is to elucidate the main determinants of foreign direct investment (FDI) in the case of the Arab Maghreb countries.

We employ a dynamic panel analysis using the General Method of Moments for a sample composed of 105 countries over the period 1985–2018.

We show that FDI stability, market size, higher education enrolment, quality of institutions, distance, sharing of common border, and bilateral investment and integration agreements are the main determinants of FDI location. These determinants are neither general. The potential for attracting FDI from AMU countries is poorly exploited. FDI to the AMU is lower than estimated stock. The observed FDI to potential FDI ratio does not exceed 87%. France and Spain are the main investors in the AMU region thanks to historical and cultural links. The FDI from the United States, Canada, Germany, Belgium, and Japan are below what is expected.

The contribution of this paper is observed on the examining oh the determinants of the FDI in the Arab Maghreb countries. Our study demonstrate that the political stability can decrease investment risk in these countries. The administrations correspondingly require expanding their rules and strategies with union demonstrations which were at the beginning of the departure and closing of several foreign companies.

The financial world of today is evolving at a rate that can be challenging to keep up with and comprehend due to developments in information and communication technology. When compared to a conventional disclosure, the eXtensible Business Reporting Language (XBRL), which was named one of the top ten accounting technologies, has a clear advantage in reducing information asymmetry by providing interactive data disclosure. This study aims to examine whether forcing companies to adopt XBRL would cause them to prefer misclassifying income statement items as an alternative to more risky earnings management methods.

The study sample includes nonfinancial UAE companies listed on Dubai Financial Market and Abu Dhabi Securities Exchange from 2012 to 2019. Fixed effect and system General Method of Moments regressions were used to analyze the study data.

The study found that XBRL reporting resulted in lowering the quality of financial reporting as companies have a higher tendency to misclassify income statement items as earnings management mechanism.

The findings of this research can be used by stakeholders and practitioners in the UAE to better understand whether the use of XBRL is linked to the engagement of financial reporting manipulative practices. The findings of this study also inform policymakers and regulators about the consequences of companies formally adopting digital disclosure language in an effort to improve the quality of their reporting. Besides, the results offer guidance to regulators considering imposing XBRL usage regulations.

Limited number of studies have tested the association between XBRL mandatory adoption and misclassification of income statement items as an earnings management tool in the Gulf Cooperation Council region.

This paper aims to explore the in-sample explanatory and out-of-sample forecasting accuracy of the generalized additive model for location, scale and shape (GAMLSS) model in contrast to the GAM method in Munich’s residential market.

The paper explores the in-sample explanatory results via comparison of coefficients and a graphical analysis of non-linear effects. The out-of-sample forecasting accuracy focusses on 50 loops of three models excluding 10 per cent of the observations randomly. Afterwards, it obtains the predicted functional forms and predicts the remaining 10 per cent. The forecasting performance is measured via error variance, root mean squared error, mean absolute error and the mean percentage error.

The results show that the complexity of asking rents in Munich is more accurately captured by the GAMLSS approach than the GAM as shown by an outperformance in the in-sample explanatory accuracy. The results further show that the theoretical and empirical complexities do pay off in view of the increased out-of-sample forecasting power of the GAMLSS approach.

The computational requirements necessary to estimate GAMLSS models in terms of number of cores and RAM are high and might constitute one of the limiting factors for (institutional) researchers. Moreover, large and detailed knowledge on statistical inference and programming is necessary.

The usage of the GAMLSS approach would lead policymakers to better understand the local factors affecting rents. Institutional researchers, instead, would clearly aim at calibrating the forecasting accuracy of the model to better forecast rents in investment strategies. Finally, future researchers are encouraged to exploit the large potential of the GAMLSS framework and its modelling flexibility.

The GAMLSS approach is widely recognised and used by international institutions such as the World Health Organisation, the International Monetary Fund and the European Commission. This is the first study to the best of the author’s knowledge to assess the properties of the GAMLSS approach in applied real estate research from a statistical asymptotic perspective by using a unique data basis with more than 38,000 observations.

The institutional framework of an African country may influence the effectiveness of the International Financial Reporting Standards (IFRS) on foreign investment inflows. The purpose of this paper is to argue that the quality of a country's institutional framework impacts the effectiveness of IFRS to an adopting country and ultimately influences the levels of Foreign Portfolio Investment (FPI).

Employing country-level data. A sample of 15 countries from Africa is used. Data is collected over a period of 22 years (1994–2014). The authors employ the General Method of Moments (GMM) panel regression technique to examine whether the quality of a country's institutional framework has an impact on the relationship between IFRS and FPI and the Propensity Score Matching (PSM) technique to assess the level of impact.

The findings reveal that the quality of a country's institutional framework moderates the strength of the association between IFRS and FPI. Overall, the authors find that the quality of the institutional frameworks in African countries has a negative effect on the IFRS and FPI nexus.

The study focuses exclusively on African countries; using an exclusively African sample limits the generalisation of results to other continents like Latin America with similar environments to Africa.

This study provide evidence that IFRS alone cannot ensure the intended capital market benefits but encourages the development of strong institutions in African countries to realise the most from IFRS adoption. The emphasis on institutional development is an essential contribution that this study makes.

This study is unique since it emphasises the importance of institutional framework quality when considering the impact of IFRS on foreign investment inflows in an African setting.