Economic growth and public and private investment returns

We study the macroeconomic effects of public and private investment in 17 OECD economies through a VAR analysis with annual data from 1960 to 2014. From impulse response functions we find that public investment had a positive growth effect in most countries, and a contractionary effect in Finland, UK, Sweden, Japan, and Canada. Public investment led to private investment crowding out in Belgium, Ireland, Finland, Canada, Sweden, the UK and crowding-in effects in the rest of the countries. Private investment has a positive growth effect in all countries; crowds-out (crowds-in) public investment in Belgium and Sweden (in the rest of the countries). The partial rates of return of public and private investment are mostly positive.

Macroeconomic rates of return of public and private investment : crowding-in and crowding-out effects

Using annual data from 14 European Union countries, plus Canada, Japan and the United States, we evaluate the macroeconomic effects of public and private investment through VAR analysis. From impulse response functions, we are able to assess the extent of crowding-in or crowding-out of both components of investment. We also compute the associated macroeconomic rates of return of public and private investment for each country. The results point mostly to the existence of positive effects of public investment and private investment on output. On the other hand, the crowding-in effects of public investment on private investment vary across countries, while the crowding-in effect of private investment on public investment is more generalised.

Performance analysis of brazilian public and philanthropic hospitals

This paper presents the results of a research that aimed at identifying optimal performance standards of Brazilian public and philanthropic hospitals. In order to carry out the analysis, a model based on Data Envelopment Analysis (DEA) was developed. We collected financial data from hospitals’ financial statements available on the internet, as well as operational data from the Information Technology Department of the Brazilian Public Health Care System – SUS (DATASUS). Data from 18 hospitals from 2007 to 2011 were analyzed. Our DEA model used both operational and financial indicators (variables). In order to develop this model, two indicators were considered inputs: Values (in Brazilian Reais) of Fixed Assets and Planned Capacity. On the other hand, the following indicators were considered outputs: Net Margin, Return on Assets and Institutional Mortality Rate. As regards the proposed model, there were five hospitals with optimal performance and four hospitals were considered inefficient, upon the analysis of the variables, considering the analyzed period. Analysis of the weights indicated the most relevant variables for determining efficiency and scale variable values, which is an important tool to aid the decision-making by hospital managers. Finally, the scale variables determined the returns on production, indicating that 14 hospitals work with scale diseconomies. This may indicate inefficiency in the resource management of the Brazilian public health-care system, by analyzing this set of proposed variables.