No abstract

Tax administration constantly monitors taxpayers through tax control to meet the legal obligations of the tax field. The main purpose of this function is to advise taxpayers and maintain operational control through continuous monitoring. Motivated by the importance of tax control, this paper aims to provide an empirical contribution to the analysis of tax control’s effects on the level of tax revenues. The database obtained in the analysis is both quantitative and qualitative according to the evidence of direct operational controls performed on businesses. The variables analysed are total tax revenues from value added tax (VAT), profit tax, personal income tax (PIT), withholding tax, etc.; tax control variables and macroeconomic variables. The methodology used in this paper is based on linear models with many variables as well as statistical tests to find the potential levels and equilibrium, elasticity and structural estimation of tax revenues. The findings of this paper provide a focused contribution on current issues for tax control policymakers, as well as other public entities, and they make an academic contribution to the legal and economic interpretation of the importance of tax control.

Ten financial institutions are offering finance leasing-loans in Albania. Even though finance leasing is a potential financing resource for small and medium enterprises in Albania (which are on average 95% of national enterprises), the value of finance leasing is one thousand times smaller than other forms of medium and long-term loans or real estate loans. Developing of finance leasing is a challenge for the progress of the financial sector, and untapped potential as well. Currently, the finance leasing portfolio is dominated by financing for personal vehicles and work-vehicles, therefore diversification of leasing products is an immediate need of consumers. This study analyzes the value of finance leasing in Albania with time series from 2008 to 2020 (with quarterly frequency). The methodology applied for data processing is the co-integration method of finance leasing and other forms of medium-term and long-term financing. Also, the ARMA method is used to forecast the value of finance leasing. We found out that there is no long-run relationship between finance leasing with medium and long-term loans. Therefore, econometric tests suggest optimal forecasting ARMA (1,1) modeling. The parameters of ARMA model are positive statistically significant with autocorrelation AR (1) and negative statistically significant with the moving average MA (1), and forecasting values have a short-run equilibrium with a wide interval.

In the developing countries, including Albania, attracting FDIs remains a government priority towards development of investments and the whole economy. Therefore, the main objective of this paper is to analyze the impact of FDIs on economic growth (GDP level) in Albania. The analysis is based on the neoclassical growth model, following the Solow model. The dependent variable in the model is the GDP level and independent variables are: capital (foreign and domestic capital investments) and labor (average salary) for the period 1996-2013 with quarterly data. The results of the econometric analysis indicate that the Solow model is applicable in the Albanian economy, showing a positive correlation which is statistically significant between the explanatory variables and the dependent variable both in the short and long run. The impact of FDIs on GDP is several times smaller than the impact of domestic capital investments. This elasticity can be explained by the lower level of FDI inflows compared to the domestic capital investments and the limitations in evaluating the "endogenous" growth of FDIs. Whereas the analysis of the sector and country of origin concentration of the FDI stock is done using the Herfindal -Hirschman index for the period 2007-2013 and the results determine a significant concentration of FDI stock, based on three sectors and a few countries of origin.

This paper analyzes long-run equilibrium of "house price index" in Tirana (the capital city of Albania) achieved by the long-run performance of macroeconomic factors.We have used the techniques and analysis of linear multiple regression by VECM (vector error correction model), to identify endogenous factors, that effect the stability of "house price index". The analyze is based on data series 2010-2018 (with 3-month frequency), with independent variables: mortgage loan, interest rate on long-term loans, construction cost index, EUR/ALL exchange rate, house price index with lag(1).We conclude that all these independent variable (expect EUR/ALL exchange rate) are statistically significant, in long-run equilibrium and in the elasticity assessment of "house price index".