DSpace Collection:https://hdl.handle.net/10316/420052024-03-29T07:07:32Z2024-03-29T07:07:32ZFertility choices, Demographics and AutomationAlmeida, DerickSequeira, Tiagohttps://hdl.handle.net/10316/1087992023-09-19T15:10:16Z2023-09-18T00:00:00ZTitle: Fertility choices, Demographics and Automation
Authors: Almeida, Derick; Sequeira, Tiago
Abstract: In this paper we study a theoretical link between the effects of increased automation on labor markets, and the fertility decisions of a representative household that is replaced by robots in the production of tasks. We develop a framework in which children provide utility and impose an opportunity cost to the household due to lost labor income. We show that fertility rate changes are the result of an optimal response to wage variations after the economy is hit by a shock that increases the design quality of robots used in production. Using this model, we characterize an initial equilibrium and simulate the effect of a 10% increase in robot productivity on important endogenous variables, including wages, and find that, in the absence of fixed costs to raising children, the fertility rate increases by approximately 3.4%.2023-09-18T00:00:00ZShort-term rentals and housing market: Evidence from portuguese metropolitan areasNobre, FranciscoGonçalves, DiogoCruz, Ronizehttps://hdl.handle.net/10316/1087162023-09-08T15:18:05Z2023-09-08T00:00:00ZTitle: Short-term rentals and housing market: Evidence from portuguese metropolitan areas
Authors: Nobre, Francisco; Gonçalves, Diogo; Cruz, Ronize
Abstract: In this paper, we make use of the rapid expansion of short-term rentals in Portugal, based on a policy change in 2014, to estimate the effects on house prices. Using a novel dataset consisting of property transaction data, from 2010 to 2017, for the metropolitan areas of Lisbon and Porto, we causally identify the impact of these reforms through a two-way fixed effects model, at the quarterly level, where we control for property specific characteristics and location and time fixed effects. The evidence suggests that a one-unit increment in the number of local lodging establishments results in a 0.17% increase in the value of transaction, which is ensured by a set of robustness exercises. Stronger effects are found for properties with four or more bedrooms, owned by citizens outside of the European Union, in the municipality of Porto and at the upper quantiles. We also document a decrease in the number of transactions of new buildings and a positive effect on the value of commercial properties.2023-09-08T00:00:00ZManagement and Human Capital Employment: an overlookedSantos, MarceloGarrido, SusanaSequeira, Tiago Neveshttps://hdl.handle.net/10316/1066732023-04-14T17:13:27Z2023-01-05T00:00:00ZTitle: Management and Human Capital Employment: an overlooked
Authors: Santos, Marcelo; Garrido, Susana; Sequeira, Tiago Neves
Abstract: We look at data for Management and Skills demand of firms in existing databases and we highlight the strong positive relationship between both variables. We devise a model that explains this relationship and calibrate it in order to present quantitative results and compare those results with the estimated ones. We discover that a simple model with Management as Technology can replicate well the estimated influence of Management in the skills demand of firms. We also present evidence of the influence of the subitems of Management on skills’ demand and discovered that aside from the talent component of Management, target and performance components greatly influence the demand for skills.2023-01-05T00:00:00ZFlip the coin: Heads, tails or cryptocurrencies?Duarte, António Manuel PortugalMurta, Fátima Teresa SolSilva, Nuno Baetas daVieira, Beatriz Rodrigueshttps://hdl.handle.net/10316/1066722023-04-14T14:17:06Z2023-03-07T00:00:00ZTitle: Flip the coin: Heads, tails or cryptocurrencies?
Authors: Duarte, António Manuel Portugal; Murta, Fátima Teresa Sol; Silva, Nuno Baetas da; Vieira, Beatriz Rodrigues
Abstract: This paper analysis and compares the volatility of seven cryptocurrencies – Bitcoin, Dogecoin, Ethereum, BitcoinCash, Ripple, Stellar and Litecoin – to the volatility of seven centralized currencies – Yuan, Yen, Canadian Dollar, Brazilian Real, Swiss Franc, Euro and British Pound. We estimate GARCH models to analyze their volatility. The results point to a considerably high volatility of cryptocurrencies when compared to that of centralized currencies. Therefore, we conclude that cryptocurrencies still fall far short of fulfilling all the requirements to be considered as a currency, specifically regarding the functions of store of value and unit of account.2023-03-07T00:00:00Z