Zimbabwe's informal sector is among the most vibrant sectors, but contributes little to tax revenue collection. The study found that although the growth of the informal sector has a positive coefficient, its contribution to tax revenue is negligible.
Introduction
In addition, the introduction of the presumptive tax was intended to restrict unregistered informal traders from complying with tax regulations and also to ease the yoke of the formal sector (ZIMRA bulletin 2011). The contribution of the revenue to the budget is considered very insignificant, despite the introduction of a presumed tax.
Background
Sixty-nine percent (69%) of the informal sector employees are in the broad age group of 20 to 39 years. As a result, the majority of the informal sector was the worst in complying with tax regulations.
Problem statement
Small businesses make the biggest contribution to the shadow economy, which operates outside the tax net. What measures, if any, can be used to ensure that the informal economy contributes to Zimbabwe's revenue pool and the results of such interventions.
Objectives
Rationale of the study
In addition, I wanted to investigate the impact of the growth of the informal sector on tax performance. This survey is important to the nation because it is aimed at improving revenue inflow to the fiscus for economic development.
Research questions
In addition, the research will help to refine the research skills of research as a learning process.
Hypothesis testing
Organisation of the study
LITERATURE REVIEW
Introduction
The informal sector and taxation
The informal sector is estimated to account for 75% of total employment in sub-Saharan Africa. Conversely, Feige (1989) argues that the HTT regime does sufficiently include the activities in the informal sector.
General overview on sub-Saharan African countries
Castells and Benton (1989) assert that the operation of informal sector activities, namely fiscal evasion causes financial losses in state revenues and ceteris paribus generates budget deficits. In comparison, the share of production and employment of the informal sector in Africa has been increasing. Taking for example, employment in the formal sector has far outstripped informal employment in Kenya and Uganda.
Furthermore, looking at southern Africa, 43 percent of urban employment in Zambia is in the informal economy, while statistics in Mozambique showed that in the 1990s, 30-40 percent of the urban population was dependent on the informal economy. The informal sector in Africa is dominated by trade-related activities, with services and manufacturing accounting for only a small percentage of the sector (UN 1996).
Informal sector and taxation in Kenya
Angola, Nigeria, South Africa and Uganda, most informal sector workers are active in retail trade (ILO 2002a). The available literature shows that there is a strong link between the informal sector and the government's inability to collect the necessary taxes. From the point of view of the informal sector, the tax compliance burden for the informal sector can be high compared to that of large companies (higher unit cost relative to turnover).
Furthermore, the cost of complying with a particular set of tax rules/regulations is generally considered to be higher for the informal sector as a percentage of turnover or profit. The main goal of the system was to attract the informal sector into the tax network by simplifying tax procedures, encouraging record keeping and tax accounting, thereby facilitating the filing of tax returns and reducing the costs of complying with tax regulations.
Informal sector and taxation in Tanzania
Nevertheless, as the economy generally grows, the informal sector may have grown in absolute terms. According to a survey conducted in Tanzania, 43% of informal operators claimed that they were already paying some form of tax. In particular, 47% of traders/hotels/restaurants claimed to pay tax and 46% of transporters.
Overall and by sector, more operators with higher incomes reported paying taxes and reported paying higher percentages of value added. Overall, 6% of the value added was reported paid to the Tanzania Revenue Authority (TRA) and 3% to local authorities, for an overall average of 4%, which is not insignificant.
Informal sector and taxation in South Africa
A recent study highlighted several important characteristics of the informal sector, important to understand in assessing opportunities for tax increases and their distributional impact. One reason informal businesses dominate trade and commerce in South Africa is the legacy of isolated and underserved areas such as informal villages outside major cities, meaning the lack of formal retail in villages and homelands under apartheid led to entrepreneurial opportunities in the informal sector. . . According to the report, a special simplified tax regime is needed for both informal and formal small businesses.
Unlike the formal sector, the informal sector is underdeveloped and, despite its potential, makes a minimal contribution to the GDP economy. This detachment ensures that the informal sector is unable to generate and support its own growth and development (Mbeki 2003).
Despite the importance of the informal sector as the main source of employment, the distribution of the tax potential of the informal sector among over 4 million individuals is very weak against certification taxation with minimal cost to the economy. This conclusion is supported by Shah (2012) who found that 75% of SMEs in the informal sector in Zambia earn less than ZMK 1 million per month. Efforts by the Zambian government to tax informality, and even public debates on the tax potential of the informal sector, have been poorly informed.
The literature and evidence on the size, evolution, structure, causes and characteristics of the informal sector in Zambia weakens effective tax policy making. Short- to medium-term measures should focus on strengthening existing taxes and mechanisms to promote the formalization of the informal sector.
Formalisation of the informal sector
Much of the early evidence that formalization can lead to faster growth comes from evidence that formal firms tend to grow faster than informal sector firms. As the broadest-based tax in Zimbabwe, VAT captures some of the transactions in the informal sector where informal sector participants purchase goods and services from the formal sector. To conclude in the long term, the tax potential of the informal sector cannot be ignored.
It would be reasonable to place the informal sector within a properly designed framework that allocates administrative resources for tax collection from this sector. To find out whether it is worth devoting more resources to informal sector taxation, we need to gain insight into how this tax potential is distributed among participants in Zimbabwe's informal sector.
Conclusion
The revenue implication of taxation on the informal sector is to ensure job creation and poverty reduction among lower income groups, long-term economic development and the development of a larger tax base over time. The pressing concern for many tax experts is that increased taxes on small firms could end up stunting growth, and that these costs could far outweigh the revenue benefit. This reason is of course compelling, and based on the concept that small firms opt for informality precisely because they believe that informality will benefit them, given the burdens of formality.
Introduction
Model specification
- General model
- Specific model
Ag = the ratio of agriculture to GDP. At=the relationship between the construction sector and GDP. Ms= the ratio of the mining sector to GDP. As mentioned earlier, the researcher chose this model specification in accordance with Chelliah's (1971) load ratio determinants. If Ty represents the predicted tax rate, it means that there is an average relationship between the predicted tax rate and the exogenous variables.
An exogenous variable multiplied by its coefficient will therefore give the base's average contribution to the tax. However, to obtain a reliable measure of tax effort (tax effort index), we divide the actual tax rate by the predicted tax rate (Chelliah, Baas, and Kelly, 1975).
Justification of the econometric model
Initially, a panel approach was chosen based on the rationale that we should be able to compare results with other countries to determine the tax effort of Zimbabwe. But the researcher decided to abandon the approach on the grounds that the main purpose of the thesis is not to predict tax performance, but to characterize the relationship between tax revenue and the increase in informal activities. Dealing with panel data compiled from Zimbabwean data and data from other countries is therefore an unnecessary effort.
Where a is the tax-to-GDP ratio of the Zimbabwean government during period t, α is the constant, is the vector of coefficients on the vector of parameters influencing the tax-to-GDP ratio, is the set of explanatory variables observed, is the error term. Using the time series data was advantageous because many observations could be included, making the sample more representative.
Discussion of the Explanatory Variables
This is due to the administrative ease and cheapness with which tax revenue can be collected in this economic sector. Therefore, it is suggested that the growth of the mining sector will have a positive effect on tax revenue. Nevertheless, the growth of the informal sector does not necessarily imply the reduction of the formal sector.
This is considered an indicator of the gray economy, which we called the shadow. One way to solve this problem is to include a dummy for each interception move.
Diagnostic Tests
- Testing for stationarity
- Tests for Model Specification and Significance of the Model
- Multicolinearity Test
- Test for Heteroscedasticity
- Test for Correlation
If the F-statistic is less than 10%, the null hypothesis that tax ratio is not determined by the independent variable will be rejected and therefore we conclude that the model is significant at 1%, 5% and 10%. OLS estimators will be unbiased and consistent when there is heteroscedasticity, but the estimators will be inefficient. If evidence of heteroscedasticity is found, OLS will be abandoned and the Weighted Least Squares (WLS) method will be used to estimate the regression.
The Durbin Watson (DW) statistic will be used to detect the presence of first-order correlation, and the Breusch-Pagan Godfrey LM test will test for higher-order serial autocorrelation. The hypothesis of no serial correlation will be rejected if nR2 is greater than Chi square (2) or if p-values are less than 10%.
Data and data sources
Conclusion
PRESENTATION OF RESULTS
- Introduction
- Descriptive statistics
- Diagnostic tests results
- Stationarity test
- Test for heteroscedascity
- Multicolinearity test
- Test for Serial Correlation
- Model Specification
- The Ordinary Least Squares Model
- Interpretation of Results
- Conclusion
Furthermore, a p-value of 0.1245 was reported indicating that the informal sector is not a significant determinant of the country's tax performance. As expected, the manufacturing sector's p-value of 0.0065 indicates that the manufacturing sector is important in explaining the variation in tax collection, thus contributing significantly to taxation. The mining sector has a positive impact on taxation from the results coefficient 0.274899 shows that a 1% change in mining causes a 0.27% change in tax collection.
The construction sector is also significant in explaining the difference in tax as determined by a p-value of 0.0734, which is significant at the 5 and 10% levels. As predicted, the share of agriculture shows a strong negative association with tax collection according to a p-value of 0.1601. In Zimbabwe, the interpretation is that a large proportion of agriculture includes a generously allocated subsistence sector.
FINDINGS, POLICY RECOMMENDATIONS AND SUMMARY OF THE STUDY
- Introduction
- Findings
- Policy Recommendations
- Suggestions for Further Research
- Summary of the study
In order to bring in some of the informal sector income that currently escapes the tax net, it is worth reducing the levels of non-compliance and also increasing the incentives of small businesses to formalize. Quantitative characteristics of developing country tax systems', In Newbery, D. eds), Theory of Taxation in Developing Countries, 205 241, New York: Oxford University Press. Alfredo (2006) The currency demand approach and the size of the shadow economy: a critical appraisal.
Enste (2000) Shadow Economies: Size, Causes, and Consequences, Journal of Economic Literature Vol. 1994) “Estimating the Size of the Shadow Economy: A Statistics Canada Perspective”, The Canadian Economic Observer 7(5). Friedrich Schneider, July 2002, The Size and Measurement of the Informal Economy in 110 Countries of the World, paper presented at the Workshop of the Australian National Tax Centre, ANU, Canberra, Australia, 2002.
