How the Crowding-out Effect Hypothesis Stands Under a Financial System Liberalised: The Mexican Economy Case

This paper revisits the financial-liberalisation hypothesis predicting one negative effect of public investment on private investment, which led to the de-regularisation of the financial system in Mexico and many other Less-developed Countries (LDCs) so as to probe whether such tenet hold today even when the role played by the public sector has evolved from having a direct intervention in credit allocation scheme to the fulfilment of a limited duties such as the surveillance of the money and capital markets under a financial liberalization environment. Considering Mexico as a case study, an econometric exercise over the 1970-2019 period is tried crunching official statistical data. Besides a brief introduction, the second section discusses theoretical issues concerning the effects of public investment on private investment, likewise some empirical work done in this field. The third section develops the methodology used to taste the net effect of public investment on private investment and presents also the results estimates. Finally, some conclusions derived from the empirical evidence found in the analysis and a brief discussion are laid down.

What Supports Startups Need From Science and Technology Parks

This study establishes strategies for the science and technology park (STP) operators to develop the support their hosted companies/startups (HCs) need to improve their performance at different stages of maturity. Unlike most of the research concentrated on the STP's viewpoints or used the after-the-fact results to create the policy guidelines for the operators, our paper uses the opposite approach by directly asking the HCs regarding what they need. From our survey results, we have identified two different strategies for improving HCs' performance. A comprehensive internal incubation network is necessary for any startup in a relatively mature development stage but with short settled years. On the other hand, a robust external incubation network is crucial for small-size startups in a low level of development stage but with long-settled years at STPs. We hope that the methodology underpinned in this study could open a new window for future research to better aid HCs in an STP.

Bank Credit Risk Rating Process: Is There a Difference Between Agencies?

The purpose of this article is to compare the bank credit risk rating (BCRR) process between credit rating agency (CRA) after the 2012 revision of their methodologies using 76 banks from 23 EMENA countries rated simultaneously by S&P's, Moody's and FitchRatings. We made this comparison based on the CAMELS model with a proposed 'S’ to BCRR. We use “ordered logit” regression for the rating classes and we complete our analysis by “linear multiple” regression for the rating grades. The results show that the BCRR processes are largely consistent between agencies but not aligned. Some differences appear in the important factors and relevant variables of the intrinsic credit quality component that manifest themselves in specific behaviors distinguishing one agency to another. The three agencies agree on the factors: Capital, Earnings, Liquidity and Supports and the most relevant support variable is the sovereign rating of the bank's country of establishment. The results also confirm a consistence between the BCRR's revealed and practiced methodologies revised by the CRA.

Modeling the Exchange Rate Volatility Using the BRICS GARCH-type Models

The paper models the performance of GARCH-type models on BRICS exchange rates volatility. The levels of interdependence and dynamic connection among the BRICS financial markets using appropriate univariate time series models were evaluated for the period January 2008 to January 2018. The results revealed the presence of ARCH effects in the BRICS exchange rates. The univariate GARCH models for the BRICS exchange rates were fitted to the data using Student t-distribution. The GARCH (1,1) model found the unconditional volatility for each of the BRICS exchange rates series while EGARCH (1,1) and TGARCH (1,1) models presented the leverage effect. Moreover, the EGARCH (1,1) model illustrated that the asymmetric effects dominate the symmetric effects except for South Africa. The TGARCH (1,1) model on the other hand revealed contrary findings. The paper recommends a study be considered to draw comparison on the different types of GARCH models on the time varying integrated data other than the ones used in the paper.

Investigating if the Financial Markets Performance Affects the Shadow Economy: Additional Evidence From EU Countries

The shadow economy also known as the informal or unobserved or underground economy, is a phenomenon that affects not only emerging markets and developing countries but also advanced economies. In general, this undeclared economic activity is hard to measure given its hidden nature in addition to its relation with unlawful activities. Nevertheless, apart from the legal aspects that may appear, shadow economy has negative implications in terms of tax revenue and social security contributions for the nations. To this end, an extensive literature has explored the measurement issues as well as the root causes of this phenomenon proving that the underground economy constitutes a significant portion of the overall economy in a number of countries. This paper tries to investigate the relationship between the shadow economy and the financial markets. This paper employs a number of panel data regression models to detect the association between the financial market metrics and the shadow economy (as a% of GDP). The outcome of this paper is that it finds evidence that increased market capitalization, GDP per capita and FDI as well as low unemployment and inflation rates contribute to low levels of shadow economy. This can be of value to policy makers and the competent authorities of the countries that wish to find means to contain their shadow economy.

Exploring the Influence of Commodity Prices, Real Exchange Rate and Trade Openness on Economic Performance in an Emerging Country

Do commodity prices, real exchange rate and trade openness influence economic growth in South Africa? This question is fundamental to academic research since it forms the basis of macroeconomic policies. Therefore, the comprehension of such a relationship is vital which has ushered this study into investigating the effect of real exchange rate, commodity prices and trade openness on economic growth in South Africa from 1984-2019. The purpose of this study is to contribute to the diverse literature on macroeconomics and international trade in the continent and the rest of the world. To achieve this, the Johansen cointegration method and Vector Error Correction Model were employed. The Johansen cointegration method confirmed the existence of a long-run relationship among the variables. Commodity prices and trade openness positively influenced economic growth while real exchange rate inversely influenced economic growth. The Vector Error Correction Model also confirmed that the disequilibrium in the model can be corrected in 1 year 9 months. The study`s findings suggest a methodical monetary policy synthesis that controls both the commodity price stability and exchange rate that spurs economic growth.

Can Multistep Nonparametric Regressions Beat Historical Average in Predicting Excess Stock Returns?

Several economic and financial variables are said to have predictive power over excess stock returns. Empirically there is little consensus among academics, whether these variables have predictive power or not. Results are often sensitive to the econometric model of choice. The econometric models can produce biased results due to the high degree of persistence in predictive variables. Apart from high persistence, the relationship between stock return and the predictive variable may also be misspecified in the model. In order to address possible non-linearities and endogeneity between the residuals and persistent independent variables in predictive regressions, multi-step non-parametric and semiparametric regressions are explored in this paper. In these regressions, the conditional mean and the residuals are estimated separately and then added to obtain the predicted excess stock returns. Goyal and Welch's (2008) predictive variables are used to predict excess S&P 500 returns. The predictive performance of both in-sample and out-of-sample of the two proposed models are compared with the historical average, Ordinary Least Squares (OLS) and non-parametric regressions. The performance of the models is evaluated using Root Mean Squared Errors (RMSEs). The explored models, particularly the two-step nonparametric model, outperform the compared models in-sample. Out-of-sample several variables are found to have predictive ability.

Bank Credit Risk Rating Process: Is There a Change With the 2007-09 Crisis?

The purpose of this article is to study empirically the bank credit risk rating (BCRR) process over time using 89 banks from 27 EMENA countries rated by S&P’s simultaneously before and after 2007-09 crises. We made this comparison based on the CAMELS model with a proposed ‘S’ to BCRR. We use "ordered logit" regression for the rating classes and we complete our analysis by “linear multiple” regression for the rating grades. The results show that the rating changes in 2012 are mainly a methodology revision consequence of the entire rating process changes, including the weight of components, the important factors and the relevant variables in order to take into account some of the lessons learned from this global crisis. They also show a consistence between the BCRR's revealed and practiced methodologies revised by the credit rating agencies (CRAs).

Combining Financial Information and Corporate Social Responsibility Related Information for Characterizing Corporate Disclosure: Some Insights From Moroccan Context

This paper deals with the corporate disclosure and therefore the option to predict the corporate disclosure through combining financial and non-financial information. In this paper, we study the corporate disclosure characteristics by investigating the predictability strength of specific financial performance indicators and corporate social responsiblity (CSR) related information. The sample of this research contains 58 organizations that had been awarded the label of the CSR in Morocco. A content analysis of corporate websites, financial statements and annual reports are used for each organization. Based on corporate disclosure content, two groups are constructed. We use four financial indicators for measuring the performance (financial information) and particular CSR related information (non-financial information) for these two groups. The discriminant analysis highlights to what extend specific information could predict the nature corporate disclosure content. As results, these indicators and information show different levels of ability to predict corporate disclosure content. Our findings, when confronted to the literature, explicit convergences about the predictability of corporate disclosure content.

Crowdfunding: New Financing Tool for Social and Solidarity Economy in Morocco

Alternative forms of financing have emerged recently, such as solidarity finance, crowdfunding and participatory finance. They provide innovative solutions to the financial problems faced by economic agents wishing to carry out projects with significant social and environmental impact.In fact, these alternative forms of financing aim at proposing unprecedented alternatives and complementary financing offers that can help the actors of Social and Solidarity Economy (SSE) to concretize their projects. For this purpose, we are developing an analysis of the major assets and the distinguished opportunities that Crowdfunding will bring to SSE actors in Morocco. We will also examine how it can become one substitute of classical finance in Morocco.