This paper develops a static model of endogenous task-based technical progress to study how factor scarcity induces technological progress and changes in factor prices. The equilibrium technology is multi-dimensional and not strongly factor-saving in the sense of Acemoglu (2010). Nevertheless, labour scarcity induces labour productivity growth. There is a weak but no strong absolute equilibrium bias. This model provides a plausible interpretation of the famous contention of Hicks (1932) about the role of factor prices and factor endowments for induced innovations. It may serve as a microfoundation for canonical macro-economic models. Moreover, it accommodates features like endogenous factor supplies and a binding minimum wage.
Using quarterly data from 2006 to 2019 (55 observations), this paper examines 18 Eurozone macroeconomic variables that represent monetary policy, external and construction sectors’ performance, economic growth, investment, households’ earnings, inflation and assesses their impact on the performance of the European listed real estate companies and REITs. Empirical results demonstrate that the European listed real estate market is strongly influenced by the supply side: the construction sector and the inflation of producers’ prices; while the demand side is strongly affected by the expansionary monetary policy of ECB. Furthermore, some primary findings propose that US expansionary monetary policy shocks have an effect on the European listed real estate market. This conclusion demands further thorough research.
The purpose of this study is to determine the relationship between monetary policy and the exchange market pressure index in Turkey for the 2002–2018 period with monthly data. To obtain the foreign exchange market pressure index, this study uses the model developed by L. Girton and D.E. Roper and is based fundamentally on the monetary approach to exchange rate determination and the balance of payments. The calculated exchange market pressure index is in accordance with the developments lived in financial markets and changes in monetary policy during the period under investigation. As for the relation between exchange market pressure index and monetary policy, a VAR model was set up and a Granger type causality analysis was carried out. According to Granger causality test results, there is a unidirectional causality running from domestic credit expansion to exchange market pressure and from domestic credit expansion to interest rate differential while there is a bidirectional causality between exchange market pressure and interest rate differential. Since increasing exchange market pressure means a depreciation of the Turkish Lira, the estimated VAR model’s results support the view that the Central Bank will increase the interest rate to temper the exchange market pressure.
The tourism-poverty alleviation nexus is becoming an increasingly significant subject of academic inquiry within the tourism economics discourse. Using time series data from the World Bank (1995–2017) in a P-ARDL model, the present study explores the relationship between tourism (receipts from exports, the travel subsector, hospitality and accommodation subsector) and poverty alleviation (final household consumption) with tourism arrivals as the control variable within the context of the BRICS group. The results suggest that receipts from the travel subsector and exports met the a priori expectation – positively influencing poverty alleviation within BRICS nations in the long run. Contrastingly, receipts from the hospitality and accommodation subsector did not meet the a priori expectation of a positive sign, with the results indicating statistical insignificance in the long run. However, receipts from the hospitality and accommodation were found to only influence poverty alleviation in the short run. Relatedly, the results suggest that increases in consumption associated with growth in tourism arrivals did not influence poverty in the BRICS. The results point to the heterogeneity of the influence of tourism on poverty alleviation, whereby certain dimensions of tourism contribute to poverty alleviation in the long run and others do so in the short run. Based on these findings it is recommended that BRICS countries harness their tourism potential and promote intra-BRICS tourism to maximise the positive impact of travel and tourism export receipts on household consumption, which catalyses poverty alleviation.
The quarterly unemployment rate from the Labour Force Survey covering Poland’s data from the first quarter 2005 to the third quarter 2019 was investigated. The issue was to reveal its stochastic structure as a trend, seasonality and disturbance and to make a prognosis. The analysed data comes from a survey based on rotational design, so the problem of possibly autocorrelated survey errors was taken into consideration. Following Harvey (2000), Pfeffermann, Feder, and Signorelli (1997), Yu and Mantel (1997) and Bell and Carolan (1998) it seemed to be of great importance to include the proper autocorrelation structure of the errors into a statistical treatment. It appeared that for Polish unemployment data that structure was not as it could have been expected. After the model was fitted to the data, a conclusion about the specificity of the unemployment rate with respect to gender was drawn. Unemployment forecast until 2020:Q4 is provided.
This essay explores the journey of humanity since the emergence of Homo sapiens 300,000 years ago. It analyses the critical role of Unified Growth Theory in resolving two fundamental mysteries that had characterized this journey: (i) The mystery of growth—why did living standards stagnate for most of human history and what led to their sudden soar 200 years ago? (ii) the mystery of inequality—what are the roots of the major surge in inequality across nations and why have these gaps widened dramatically over the past 200 years?
The Israeli economy in the first two decades of the 21st century is an example of an economic transformation that may serve as a role model for addressing many challenges to economic growth. Data from this period have shown significant developments in economic growth over this relatively short period of time and indicate that these advances are attributable to policies targeting inflation, labor force participation and education. While challenges remain—including economic inequality, suboptimal health care and the threat of coronavirus pandemic to global growth—we explore developments evidenced to promote economic growth.
A modern effective business model involves the use of an appropriate pricing strategy. However, what matters is not only short-term profitability but also the long-term loyalty of clients. The main purpose of this paper is to present a specific transactional pricing strategy for a second-hand goods resale exchange platform that allows to avoid the possible negative outcomes of being associated with consumer discrimination. Using a simulation modeling approach, it was shown how customer segmentation combined with transactional pricing can help gain higher profitability. The model is based on the work of intelligent agents that recreate the full product lifecycle. Changing the input parameters of the model, it is possible to simulate different scenarios of a company’s activity and market conditions. The model supports the inclusion of any number of products, while its intelligent agents’ methods are still flexible to be replaced with other techniques. The simulation model has shown that the use of transactional pricing can increase the profitability of a business while keeping its clients loyal.
The problem of small area prediction is considered under a Linear Mixed Model. The article presents a proposal of an empirical best linear unbiased predictor under a model with two correlated random effects. The main aim of the simulation analyses is a study of an influence of the occurrence of a correlation between random effects on properties of the predictor. In the article, an increase of the accuracy due to the correlation between random effects and an influence of model misspecification in cases of the lack of correlation between random effects are analyzed. The problem of the estimation of the Mean Squared Error of the proposed predictor is also considered. The Monte Carlo simulation analyses and the application were prepared in R language.
The paper presents a method of detecting atypical observations in time series with or without seasonal fluctuations. Unlike classical methods of identifying outliers and influential observations, its essence consists in examining the impact of individual observations both on the fitted values of the model and the forecasts. The exemplification of theoretical considerations is the empirical example of modelling and forecasting daily sales of liquid fuels at X gas station in the period 2012-2014. As a predictor, a classic time series model was used, in which 7-day and 12-month cycle seasonality was described using dummy variables. The data for the period from 01.01.2012 to 30.06.2014 were for the estimation period and the second half of 2014 which was the period of empirical verification of forecasts. The obtained results were compared with other classical methods used to identify influential observations and outliers, i.e. standardized residuals, Cook distances and DFFIT. The calculations were carried out in the R environment and the Statistica package.