Non-Performing Loans and Macroeconomics Factors: The Italian Case

The purpose of this work is to investigate the influence of macroeconomics determinants on non-performing loans (NPLs) in the Italian banking system over the period 2008Q3–2020Q4. We mainly contribute to the literature by being the first empirical article to study this relationship in the Italian context in the recent period, thus providing fresh evidence on the macroeconomic impact on NPLs, i.e., on the credit risk of Italian banks. By employing the Autoregressive Distributed Lag (ARDL) cointegration model, we are able to investigate the short and long-run effects of macroeconomic factors on NPLs. The empirical findings show that gross domestic product and public debt have a negative impact on NPLs. On the other hand, we find that the unemployment rate and domestic credit positively influence impaired loans. Finally, we find evidence of the “gamble for resurrection” approach, i.e., Italian banks tend to support “zombie firms”.

Impact of Macroeconomic Indicators on the Yuan-SDR Exchange Rate

The paper endeavours to explore the macroeconomic impact on the Yuan SDR exchange rate of China during 2017m1-2021m6 to justify the internationalization of RMB which had entered into the SDR basket of IMF in October 2016.To evaluate the impact ,the paper used the methodology of Johansen (1988) cointegration and vector error correction model considering monthly Yuan per SDR as dependent variable and monthly GDP, inflation rate, foreign exchange reserves, export and import as the independent macro-economic variables. The pattern of trendline of Yuan per SDR is found nonlinear having cyclical fluctuations and seasonal variations according to Hamilton (2018). The paper also found that Yuan per SDR has significant long run causalities with export, import, inflation rate, GDP and foreign exchange rate of China during the specified period. Even, Yuan per SDR has significant short run causality with export only. The cointegrating equation converged towards the equilibrium with the speed of adjustment 11.83% per month significantly. The impulse response function of import to Yuan per SDR showed significantly convergent. The VECM contains autocorrelation problem and unit root for which it is non-stationary.

What drives the healthcare sector's economic impact? Evidence from European countries

PurposeWith high public debts and suffering economies after the COVID-19 pandemic, governments will look for ways to promote recovery. Literature substantially reports on the favorable macroeconomic impact of the healthcare sector.Design/methodology/approachThe authors use data on 19 European countries. Over 30 variables are analyzed to find factors that foster or suppress the economic impact of the healthcare sector. The economic impact is thereby expressed through five types of total multipliers, acting as dependent variables. The authors estimate multiple econometric models.FindingsThe results indicate factors that intensify or reduce the economic impact of the healthcare sector as they cause the value of one or more economic multipliers to augment or to diminish. Positive effects are expected from the growth of public funds' share in total healthcare expenditure leading to a higher output, income and value-added multipliers. The import multiplier diminishes when expenditure on healthcare as percent of GDP rises. On the other hand, rising expenditure on pharmaceuticals in the share of healthcare expenditure lowers the output multiplier. Rising GDP per capita and higher healthcare systems' technical efficiency cause the employment multiplier to lower.Originality/valuePolicymakers can strengthen the economic impact of the healthcare sector on the national economy. This could be achieved by stimulating factors, being identified in our study. Strengthening the economic impact of the healthcare sector is especially welcomed when fostering economic recovery is needed.

The NEMESIS Macro-Econometric Model

This Chapter presents the NEMESIS macro-econometric model. This model has been used for several ex-ante and ex-post evaluations of the macroeconomic impact of EU R&I policies. After a general overview of the model, a thorough description of the representation of innovation in the model is provided. As an example of its workings, an application to the interim evaluation of the Horizon 2020 programme is also provided.

Taking Stock

This Chapter presents the EU policy context that underlies the need for macroeconomic modelling for the conduct of impact evaluations of R&I funding programmes and provides a critical summary and comparison of the different ex-ante macroeconomic impact assessments of the Horizon Europe Framework Programme 2021-2027 presented in the previous three chapters. In particular, it focuses on the results obtained with the three different modelling approaches apdopted, and links them to the dissimilar properties of each of these models.

Other Innovation Policies and Alternative Modelling Approaches

This chapter discusses the macroeconomic impact evaluation of other policies related to innovation. In particular, two examples are shown on the impact simulation of a reduction to firms’ entry barriers and an increase in R&D tax credits. Alternative ways of modelling these two types of policy shocks are also provided to illustrate how different modelling platforms featuring different economic mechanisms can complement each other and enrich the landscape of macroeconomic policy impact assessments.

Empirical Analysis of the Macroeconomic impact of Foreign Aid on Pakistan Economy (1972-2014)

Purpose: Although Pakistan receives large quantity of foreign aid, like other developing countries, but it remains more dependent on foreign assistance for economic development since independence. This situation has commenced a vigorous discussion on aid-growth effectiveness. Methodology: This research work evaluates the macroeconomic impact of foreign aid on Pakistan economy by using secondary data. The empirical analysis is based on ARDL cointegration approach after testing for unit root, using the data for the period 1972-2014. Findings: The findings suggest there is no long run relationship between Foreign aid and Economic Growth. However, there exists negative short run relation between Foreign aid and Economic Growth of Pakistan. Implications: Based on the study findings, the study recommends that government of Pakistan should find alternate sources of financing as the relation between foreign aid and economic growth is found negative and insignificant. The in depth analysis of the study made it evident that allocation of aid to those sectors of the economy which really needs development, is more productive, provided that the country should use aid funds in the right direction, as corruption less economy prosper more rapidly.