CEF.UP – WiP Webinar

Friday – February 26^th, 2021 at 2:00 p.m.

“The Agglomerative Force of Education”

Jorge Saraiva – CEF.UP

Abstract:

“We find that, when skilled workers are allowed to choose their location, an economy with a higher human capital favours the agglomeration of economic activities and reduces the likelihood of a symmetric dispersion scenario. We explore the possibility that both skilled and unskilled populations remain unchanged while allowing skilled workers to increase their productivity. The choice of the productivity level turns out to be independent of spatial distribution and transportation costs. Education is higher, the higher the expenditure share in the industrial good is. Increases in education levels lead to positive externalities that affect the whole society.”

CEF.UP – WiP Webinar

Tuesday – March 23^rd, 2021 at 3:00 p.m.

“How does inequality affect growth on the US and France? A SVAR approach with structural breaks focused on the whole distribution of income and wealth”

Pedro Lima – FEP

Abstract:

“We analyze transmission channels between inequality and growth on the US and France using an approach that innovates twofold: (i) analyzing measures that characterize different parts of the income and wealth distributions; (ii) conducting a time series analysis using a SVAR approach with long-run restrictions that considers the presence of structural breaks in the data. We find that each transmission channel is affected by changes in particular parts of the income and wealth distribution, which are not always consistent with an inequality increase, and there are stark differences in the way each transmission channel operates between different distributions and countries. Our results are robust to alternative long-run specifications and provide an additional explanation for the myriad of results found in the literature that reinforces the complexity of the inequality-growth relationship.”

CEF.UP – WiP Webinar

Tuesday – April 13^th, 2021 at 3:00 p.m.

“Building a Composite Index using the Multi-objective Approach: An application to the case of human development”.

Elif Öztürk – FEP

Abstract:

“Composite indicator (CI) is a powerful tool to observe the performance of various alternatives when several dimensions are in question. Normalisation, weighting and aggregation are known as the three obligatory steps to build a CI. The current paper proposes a new and unconventional method, which does not require any of these steps, to construct a CI. In this method, we suggest using the Pareto frontier concept, a term in the multi-objective optimisation, to set the solutions  (e.g. countries, firms, or alternatives) in an order. Pareto frontiers help to collect similar solutions together according to their performance on several dimensions, sequentially. Each Pareto frontier represents a different achievement level. However,  it is not possible to evaluate the solutions located in the same Pareto frontier using multi-objective optimisation. To identify the performance of each solution within the Pareto frontiers, we implement the ordered probit regression model and predict the latent variable that represents the specific problem by using the estimated results. We use this proposed methodology to re-measure human development. A comparison took place between the Human Development Index (HDI) and our proposed method. According to the results, the country ranks in the proposed method show a significant difference compared to the HDI, although there is a high Spearman’s rank correlation. This method is strong and reliable because it does not require any vague selection of obligatory steps to build a CI. Moreover, it provides fully non-compensatory results and an influential ranking of the solutions.”

CEF.UP – WiP Webinar

Tuesday – May 4^th, 2021 at 3:00 p.m.

“Automation, Education and Demographic Dynamics: Growth Effects in an OLG Model of Endogenous Fertility”.

Catarina Peralta – FEP

Abstract:

” We address two main structural changes occurring in developed countries: the rise of automation and population ageing. We use an R\&D-based growth model in an OLG framework with endogenous education and fertility, and automation in the production process. Our model is able to combine the growth of real wages over time and either a fall or an increase in birth rates, consistent with recent data regarding the birth rate by skill group. Moreover, our model allows for the study of the interplay between the effects of population ageing and those of automation. The results show a dynamics consistent with the US trends for the period covering 1970 to 2019.”