American Journal of Interdisciplinary Research and Development ISSN Online: 2771-8948 Website: www.ajird.journalspark.org Volume 28, May - 2024 233 | P a g e DIRECTIONS FOR IMPROVING THE PROCESS OF PERSONAL INCOME TAX FORECASTING Aybek Nazarbaevich Abdullaev Inomjon To‘raevich Jumaniyazov Mirza Qilichbayevich Sabirov Shavkat Bayramovich Babaev PhD, Associate Professor International School of Finance Technology and Science, Tashkent, Uzbekistan Abstract This article reflects the problems of foreign experience in forecasting tax revenues from personal income tax and a methodological approach to further improvement of this process. Keywords: Taxpayers, source, budget, state, tax regime, tax status, income tax, ordinary resident, personal income, tax rate, tax base, declaration, tax deductions, fiscal year. Introduction Correct determination of state budget revenues, which are the main source of social services in the financial policy of the state, and ensuring proportionality in the expenditure policy in accordance with it, remain relevant as the main functions of all countries in the world. In 2023, the gross domestic product (GDP) of Uzbekistan for the first time amounted to 1 quadrillion 66 trillion 569 billion soums. Last year, the country's GDP grew by 6 percent and reached 90.9 billion dollars (average exchange rate is 11,737 soums). This number corresponds to 2.5 thousand dollars per capita [1]. According to the forecast for 2024, the rate of economic growth is 5.6–5.8 percent. In 2025– 2026, economic growth rates are expected to increase to 6.2 percent and 6.4 percent, respectively. The 2024 State Budget is dedicated to revenue, expenditure and deficit forecast. State budget revenues are forecasted in the amount of 270,703 billion soums. An increase in tax and non-tax revenues to the budget is forecasted against the background of a decrease in the overall tax burden. Correctly determining the income of the state budget, which is the main source of social services in the financial policy of the state, and, in accordance with it, ensuring proportionality in the cost policy, maintains its relevance as the main functions of all states in the world. The preservation of instability in the world market, the increase in total external and internal debt on a global scale, are taking their toll on the state budget. Currently, the forecasting of income tax from individuals is carried out by means of indicative methods based on macroeconomic indicators. In this case, the basis for predicting tax revenues to the budget is considered macroprudential indicators that affect the tax base, and this methodology is effective in stable situations in the economy. Accordingly, in the American Journal of Interdisciplinary Research and Development ISSN Online: 2771-8948 Website: www.ajird.journalspark.org Volume 28, May - 2024 234 | P a g e context of the introduction of medium-term fiscal policy and the representative tax system, combined methods of medium-term forecasting of taxes from individuals to the state budget, the use of simulation, deterministic, adaptive modeling methods based on the trend of dynamic series in the short- and medium-term forecasting of tax revenues by individual tax types in this regard is one of the important directions of scientific research. Literature Review E.Sheredko and M., who conducted scientific research on the forecast of personal income tax. The Pinskayas approached this problem from the point of view of placing human capital in the regions. L. Koroleva, T. Ermoshinalar, in their research, assessed the factors affecting tax revenues to local budgets based on normative allocations in the forecast of personal income tax [2,3]. V. Korostoleva analyzed the factors affecting the income tax collected from individuals using different methods. M.V. Pyltsina, A.G. Kazmina, I.V. Orobinskaya carried out an assessment of additional opportunities in the process of forecasting the personal income tax, while E.E. Smirnova studied the issue of the effectiveness of the tax administration in the forecasting of this type of tax [4-6]. Also, Russian scientists D. Kolodin and S. Popkov paid attention to the issues of implementation of the personal income tax forecast based on the address of residence of taxpayers, and N. I. Cherharova showed the assessment of tax revenues based on the probabilistic model of income tax forecasting. A.G. Kazmin, I.V. Orobinskaya, L.P. Koroleva, T.V. Ermoshina have also paid a lot of attention to the issue of forecasting income tax from individuals in their research. If we pay attention, in the scientific studies carried out on the forecasting of taxes from individuals, the income tax takes priority, namely, in the scientific studies of A.S. Kokin, A.V. Edronov, the importance of correlation and regression analysis in forecasting the income tax was shown. V.Edronov's research is based on the importance of the forecast of income tax from individuals in the formation of medium-term budgets in the territorial entities of Russia. In addition, the foreign scientists M. Rubin, Dj. Peters, N. Mantella, P. Span and M. Pearson's scientific research also give a wide place to the forecast of taxes collected from individuals, including income tax [7-14]. Research Methodology In the scientific-analytical study of scientific research on tax policy, in the process of forecasting the income tax from individuals, correlation-regression analysis was carried out and forecast indicators were relied on using the econometric model. Scientific and practical proposals were formed based on complex analyzes by successfully applying various methods of the process of forecasting personal income tax in foreign countries. Improvement of theoretical-methodological and methodical apparatus for ensuring the accuracy of the forecast indicators of tax revenues within the framework of taxes paid by individuals in the American Journal of Interdisciplinary Research and Development ISSN Online: 2771-8948 Website: www.ajird.journalspark.org Volume 28, May - 2024 235 | P a g e planning of budget revenues, allows to use them more effectively in scientific research within the scope of this topic. Analysis аnd Results Direct taxation of personal income of individuals exists in almost all countries, and now there is a shift towards increasing its share in state budget revenues. However, despite the importance of personal income tax, the experience of internal regulation in this part remains imperfect, because: the importance of the tax burden on individuals is high; the mechanism for providing tax credits for personal income tax does not meet the principle of social justice; problems of tax administration are not sufficiently developed; there are problems of personal income tax rate optimization. First of all, it should be noted that income tax in each country has its own characteristics due to historical, political, economic and other factors. In particular, in Great Britain, the home of the income tax, a modern system of personal income taxation was introduced through the tax reform of 1973. The taxation regime in the UK directly depends on whether an individual has resident, ordinarily resident or domiciled status [15]. Ordinarily resident" - a person who has lived in Great Britain for more than three years or a person who has expressed his intention to stay for more than three years after arriving in the country. Domicile status is determined according to the concept of British law: if a person is born in the United Kingdom, he or she has permanent residence in the United Kingdom if he or she is born to British parents [16]. In the United States, income tax is a part of federal taxes, state taxes, and local taxes, which means it is distributed among all branches of government. Income tax is paid on the basis of individuals and sole proprietorships and partnerships that are not related to legal entities. Individuals have different tax statuses, with appropriate deductions: married couples filing a joint return; married couples filing separate tax returns; family heads; single taxpayers; widows, widowers. Work clothes, transportation and other expenses directly related to the production activity of both the persons engaged in business activities and those who are employed are deducted. Certain types of income are excluded in whole or in part: 50 percent of the income from the sale of long-term capital assets, interest on bonds issued by state or local governments, and certain types of payments from public and private social insurance funds. The taxpayer can use the income instead of the usual deductions to account for expenses by items: personal debts and interest on mortgage debts as property collateral; medical expenses; contributions to charitable funds; training, travel expenses; state taxes and local taxes; costs of moving to a new place of residence [17]. France has a wide system of tax exemptions: professional, family, social, property. As the income tax rate in France is progressive, the amount of withholding may affect the applicable rate. In addition, in France there is a category of people who are completely exempt from paying this tax - an individual with an income below a certain income, and until January 1, 2021, in Russia, every individual is obliged to pay a tax of 13%, regardless of the amount of American Journal of Interdisciplinary Research and Development ISSN Online: 2771-8948 Website: www.ajird.journalspark.org Volume 28, May - 2024 236 | P a g e salary. From January 1, 2021, incomes over 5 million rubles will be taxed at a tax rate of 15% [18,19]. If we analyze the state of forecasting of revenues from taxes on individuals, among the above-mentioned countries, the experience of the Russian Federation is more advanced, it is of particular importance due to the fact that forecasting methods and calculation methods have been determined on the basis of clear and relevant regulatory documents, and as a legal basis for this, the future of the Russian Federation it is carried out on the basis of the forecasting methodology[20] of receipts to the aggregate budget for the financial year and planning period. The calculation of the forecast volume of taxes from individuals is carried out according to the direct calculation method based on the direct use of indicators, rate levels and forecast indicators of other indicators (tax credits, collection rate, etc.). The projected amount of tax collected from the income of individuals is calculated taking into account the reduction of taxes in the form of tax credits and non-taxable income recorded in the taxable base as a result of the application of benefits and preferences provided for by the current legislation on taxes and levies. The forecast of income of transport taxes from individuals is carried out by the tax authorities taking into account the deadlines for sending a tax return and paying the tax in accordance with the tax code. The forecasting methodology is developed on the basis of uniform approaches to forecasting revenue for the current fiscal year, the next fiscal year, and the planning period. The forecasting methodology for the current financial year includes, among other things, the use of data on the actual revenue receipts for the previous months of the current year. Correlation-regression analysis was carried out on the basis of personal income tax, and forecast indicators were developed using an econometric model. In this case, the factors affecting the personal income tax are calculated as gross domestic product, the number of personal income tax payers, the number of individuals who submitted personal income tax declarations, the average nominal wage, the average tax rate and the inflation rate by selecting a regression and correlation model. The construction consists of forecasting based on this model. The study concluded a data-driven multi-factor regression and correlation econometric model. In the construction of these models, we use the program "Eviews 10", which is currently widely used in econometrics. When drawing up a multi-factor regression and correlation econometric model, the resulting factor was the income tax (it) from individuals and the factors affecting it, the gross domestic product (GDP), the number of individuals income tax payers (NIT), the number of individuals income tax filing declarations (NFIT), the average nominal salary (ANW), the average tax rate (ATR), and the inflation rate (IR),: H1 – gross domestic product depends on the growth of personal income tax revenue and has a high impact; H2 – the number of personal income tax payers is highly dependent on the growth of personal income tax revenue; American Journal of Interdisciplinary Research and Development ISSN Online: 2771-8948 Website: www.ajird.journalspark.org Volume 28, May - 2024 237 | P a g e H3 – the number of personal income tax filers depends on the growth of personal income tax revenue and has a high impact; H4 – average nominal wage growth depends on the growth of personal income tax revenue and has a high degree of influence; H5 – the change in the average tax rate depends on the increase in personal income tax revenue and has a high level of influence; H6 – The change in the inflation rate depends on the increase in personal income tax revenue and has a high level of influence; Based on the above hypothesis, the following mathematical functions were formed: 𝐼𝐼𝑇 = 𝛼 + 𝛽0𝐺𝐺𝐷𝑃 + 𝛽1𝑁𝑁𝐼𝑇 + 𝛽2𝐹𝑁𝐹𝐼𝑇 + 𝛽3𝐴𝐴𝑁𝑊 + 𝛽4𝑇𝐴𝑇𝑅 + 𝛽5𝐼𝐼𝑅 + 𝜀𝑖 (1) Here: 𝐼𝐼𝑇- the factor is income tax revenue from individuals; 𝐺𝐺𝐷𝑃- gross domestic product; 𝑁𝑁𝐼𝑇- number of individual income tax payers; 𝐹𝑁𝐹𝐼𝑇- the number of individuals who filed income tax returns; 𝐴𝐴𝑁𝑊- average nominal wage; 𝐼𝐼𝑅- inflation rate; The above multi-factor regression and correlation econometric model is implemented using the "ordinary least squares" method. Before constructing a multivariate regression and correlation econometric model, there is some degree of correlation between the selected factors, which raises the problem of multicollinearity[21]. As a result, the main effect on the non-volitional variable is to cause the influence of the volitional variable to disappear. Based on this, in order to solve the problem of multicollinearity, we created a correlation matrix of selected variables, this correlation matrix is expressed in the following table (table 1.1). Table 1.1 Correlation matrix between variables affecting personal income tax1 Indicators lnIT lnNFIT lnGDP lnATR lnNIT lnANW lnIR lnIT 1.000000 lnNFIT 0.895929 1.000000 t-statistics 5.704821 probability 0.0005 lnGDP 0.966501 0.921170 1.000000 t-statistics 10.65084 6.695076 probability 0.0000 0.0002 lnATR -0.807861 -0.501261 -0.671571 1.000000 t-statistics -3.876960 -1.638493 -2.563621 probability 0.0047 0.1400 0.0335 1 Author development. American Journal of Interdisciplinary Research and Development ISSN Online: 2771-8948 Website: www.ajird.journalspark.org Volume 28, May - 2024 238 | P a g e lnNIT 0.356926 0.211579 0.235388 - 0.636924 1.000000 t-statistics 1.080723 0.612297 0.685025 -2.336790 probability 0.3113 0.5573 0.5127 0.0477 lnANW 0.972674 0.947409 0.994270 -0.668710 0.256902 1.000000 t-statistics 11.84946 8.373305 26.30744 -2.543832 0.751864 probability 0.0000 0.0000 0.0000 0.0345 0.4737 lnIR 0.625675 0.480436 0.688556 -0.508778 -0.026079 0.630741 1.000000 t-statistics 2.268571 1.549411 2.685573 -1.671560 -0.073787 2.298998 probability 0.0530 0.1599 0.0277 0.1332 0.9430 0.0505 The analysis of data in Table 1.1 shows that among the private correlation coefficients, the closest relationship is observed between the average tax rate (lnATR) and the number of personal income tax payers (lnNIT) variables. The correlation coefficient between them is - 0.636924 and has an inverse relationship. Moreover, there is a close relationship between the variables Gross Domestic Product (GDP) and Average Nominal Wage (ANW), with a correlation coefficient of 0.994270. Also, the gross domestic product (GDP) and inflation rate (IR) variables are closely related and have a correlation coefficient of 0.688556. A tight connection of variables leads to a reduction in the level of influence of other variables. Therefore, we form a multivariate regression model, omitting the voluntary variables that have a strong connection, but are not affected by the personal income tax revenue (IT), which is considered an involuntary variable (Table 1.2). Table 1.2 Results of multivariate regression and correlation analysis based on Eviews software2 Involuntary variable: lnIT Arbitrary variables Coefficient Standard error t-statistic Probability (P-value) lnGDP 0.367359 0.097625 3.762983 0.0094 lnNFIT 0.304874 0.097234 3.135465 0.0202 lnATR -2.233020 0.328843 -6.790541 0.0005 C 5.987236 1.216507 4.921662 0.0027 Coefficient of determination 0.992439 Mean value of dependent variables 8.144312 Adjusted coefficient of determination 0.988659 Standard deviation of dependent variables 0.570421 Standard error of the regression 0.060747 Akaike's criterion -2.475021 Sum of squares of residuals 0.022141 Schwartz criterion -2.353986 2 Author development. American Journal of Interdisciplinary Research and Development ISSN Online: 2771-8948 Website: www.ajird.journalspark.org Volume 28, May - 2024 239 | P a g e The value of the maximum similarity function 16.37510 Hannan-Quinn criterion -2.607795 F-statistics 262.5216 Darbin-Watson statistics 2.553175 Probability (F-statistic) 0.000001 Based on the above calculations, the following multifactor regression model was formed. ln𝐼�̂�=5.987236+0.367359lnGDP+0.304874lnNFIT-2.233020lnATR+ε (2) The coefficient of determination created in the model shows that 99 percent of the personal income tax (IT) depends on the factors formulated in the model: gross domestic product (GDP), number of personal income tax filers (NFIT) and average tax rate (ATR). The remaining 1 percent depends on other factors that have not been taken into account. The influence of personal income tax (IT) on gross domestic product (GDP), number of personal income tax filers (NFIT) and average tax rate (ATR) was determined with a coefficient of 5% significance [22]. The coefficients of the regression model of gross domestic product (GDP), number of personal income tax filers (NFIT) and average tax rate (ATR) have a P-value probability of less than 0.05, and these coefficients indicate personal income tax (IT) shows that it affects the change. The probability that the P-value of Fisher's F-statistic of the constructed regression model is less than 0.05 depends on a single change in the independent variable factors of gross domestic product (GDP), number of personal income tax filers (NFIT) and average tax rate (ATR). shows that the variable affects the estimated personal income tax (IT) [23,24]. In summary, a 1% increase in GDP increases personal income tax (IT) revenue by 0.36%, and a 1% increase in the number of personal income tax filers increases personal income tax revenue by 0.30%. leads to growth. However, a 1 percent increase in the average tax rate would reduce personal income tax revenue by 2.23 percent. Neglecting other factors, a 1% increase in GDP, the number of individuals filing personal income tax returns, and the average tax rate would result in a 1.57% decrease in personal income tax revenue [25]. Research Methodology Having studied the international experimental process of tax forecasting, we have revealed that this process has the following characteristics: firstly, forecasting of tax revenues, including personal income taxes, differs primarily based on the organization of the administration in each country's financial policy; secondly, the bodies implementing the tax revenue forecasting process are different districts; thirdly, it is distinguished by the formal designation of the methods used in the implementation of the forecasting process; fourth, the selection of the main influencing factors or indicators in forecasting tax revenues is mutual; American Journal of Interdisciplinary Research and Development ISSN Online: 2771-8948 Website: www.ajird.journalspark.org Volume 28, May - 2024 240 | P a g e fifth, there is not the same approach in developing short-, medium-, and long-term forecast indicators for tax revenue forecasting. Tax systems in many countries have evolved over a considerable period of time and have been influenced by various economic, political and social factors. Therefore, tax systems in different countries differ not only in the types and composition of taxes, rates, collection methods, but also in the tax-budget powers of the authorities and the benefits provided. Conclusion/Recommendations The following conclusions were formed as a result of researching the theoretical and methodological bases of forecasting personal income taxes: The scope of the forecast process, the goals and objectives set before it will also depend on the economic system. With the nature of the forecast in the planned economy, the scale of the forecast in the economic system, which is based on mixed market relations, and the goals and objectives set before it, are fundamentally different. From the forecast, the main goal and its tasks are also set and should be based on the economic policy of the state. 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