LEF 2023
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Browsing LEF 2023 by Author "Benešová, Irena"
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- ItemAddressing Income Inequality in Vietnam’s Northern Midlands and Mountains: A Focus on Fiscal Policy Factors(Technická Univerzita v Liberci, ) Ho, Lien H.; Benešová, Irena; Ekonomická fakultaThe Northern Midlands and Mountains constitute one of Vietnam’s six economic regions, yet it faces the lowest average income among the top 3 regions, with an average of only 1.613.000VND/month in 2014. Moreover, this region experiences the highest level of income inequality, as indicated by a Gini index of 0.42 in 2020. The study highlights that increased income inequality can lead to a decline in the region’s economic growth, significantly impacting the province’s GDP. The research emphasizes income redistribution as one of the essential functions of fiscal policy, alongside its roles in supporting macroeconomic stability and promoting overall growth. This research analyses and identifies the interplay between fiscal policy factors and income disparity to tackle the Northern Midlands and Mountains income inequality. The study utilizes panel data compromising 7,980 observations. Notably, the findings underscore the potential of increased investment and enhanced household education as critical factors for improving income inequality and fostering economic growth in the region. By considering these factors, Vietnamese economic strategists can devise effective measures to mitigate inequality and foster sustainable regional development.
- ItemApplication of VAR Model to Determine Sustainability of Short-Term Rental Accommodation(Technická Univerzita v Liberci, ) Guth, Karel; Aišmannová, Tereza; Benešová, Irena; Ekonomická fakultaPlatforms like Airbnb have fundamentally reshaped the hospitality sector as we have known it. With its distinctive model, short-term rentals (STR) have gained significant popularity among tourists and property owners alike. As the popularity of STR continues to grow, questions arise regarding its implications for sustainable tourism. In this paper, we investigate the impact of short-term rental accommodation on residential housing prices in the centre of Prague by employing an econometric analysis of time series. For this purpose, we apply the vector autoregressive (VAR) model. In the modelling, we use data on the numbers and locations of Airbnb listings alongside data on the average housing price per square meter. Other variables did not prove to be statistically significant in the equations. Firstly, the variables need to be tested for stationarity. Based on the detection of non-stationarity in the time series, the data are then transformed using the first differences. Finally, the variables are suitable for the estimation of their parameters. Subsequently, we present an impulse response analysis and plot a forecast. The prediction is then subject to the ex-post comparison, which visualises how the prognosis of the VAR model correlates with the real values.