Researching the Main Causes of the Romanian Shadow Economy at the Micro and Macro Levels: Implications for Sustainable Development
Abstract
:1. Introduction
2. Theoretical Considerations and Hypothesis Development
- HA1: Monitoring the unemployment rate contributes to sustainability through the achievement of Sustainable Development Goal 8: Decent work and economic growth.
- HA2: Monitoring the employment rate and its components (the self-employment rate and part-time employment rate) contributes to sustainability through the achievement of Sustainable Development Goal 8: Decent work and economic growth.
- HA3: Monitoring the real growth contributes to sustainability through the achievement of Sustainable Development Goal 8: Decent work and economic growth.
- HB: Monitoring the government efficiency contributes to sustainability through the achievement of Sustainable Development Goal 16: Peace, justice and strong institutions.
3. A Brief Overview of the Main Estimates of the Romanian Shadow Economy
4. Measuring Progress toward the Sustainable Development Goals—the Case of Romania
5. Identifying the Main Causes of the Romanian Shadow Economy
5.1. Data and Methodology
5.2. Empirical Results
5.2.1. The Sample Profile of Romanian Entrepreneurs
5.2.2. Highlighting the Opinions of Romanian Entrepreneurs Regarding the Romanian Shadow Economic Activity
- There is a high level of tolerance for bribery and tax avoidance, which is a common behavior among Romanian mangers.
- The lack of trust in public officials was associated with a high level of dissatisfaction regarding tax policies and business legislation, which is related to a higher level of shadow economy.
- A poor quality of business legislation, the government’s tax policy, and little government support for entrepreneurs led to an increase in shadow economic activity.
- High social contributions determined whether companies hired workers without legal forms.
- A relatively high level of corruption, anti-competitive practices of other competitors, political instability, high tax rates, and a certain uncertainty about regulation policies also led to an increase in the unofficial sector.
5.2.3. Identifying the Main Determinants of the Romanian Shadow Economy Using the MIMIC Model
5.2.4. Emphasizing the Main Implications of the Shadow Economy for Sustainable Development
5.2.5. Computing the Size of the Romanian Shadow Economy
- is the index of the SE computed by Equation (3).
- is the exogenous estimate of the SE.
- is the value of the index computed by Equation (4) in 2005.
- is a measure that is used to make the conversion from the base year to current GDP.
- is the estimated SE as a percentage of official GDP.
6. Conclusions and Further Research
6.1. Main Conclusions and Suggestions for Future Work
6.2. Policy Implications
- (1)
- Reducing the administrative burden of businesses. This involves simplifying the procedures for obtaining licenses and authorizations by accelerating the release of documents required for entrepreneurship, reducing bureaucratic barriers for such documents, and increasing the transparency of the whole process.
- (2)
- Increasing the amount of fines for companies that practice informal economic activity; specifically, penalties for the non-compliance with labor regulation.
- (3)
- Enforcement of institutions responsible for labor inspections and controls.
- (4)
- Increasing the number of information campaigns.
- (5)
- Introduction of more electronic instruments of contract registration.
- (6)
- Enforcement of penalties for situations where undeclared work is considered as ‘significant’.
- (7)
- Discouraging the use of cash by increasing the popularity of electronic payments. In the last period, the ratio of currency in circulation as a % of GDP was almost 60%, revealing a level that was six times higher than the level recorded by the countries of the Eurozone. In 2013 in Romania, a person makes on average 4.3 electronic payments (excluding card payments and including applications such as internet banking, home banking, mobile banking, electronic transactions made at ATMs) annually, which was about 18 times less than the European Union (EU) average and 11 times less than the average in the Central and East European countries, placing Romania in the last position of the ranking of EU countries. Also, a person makes on average 9.4 card payments annually, which is about 10 times less than the EU average and five times less than the average in the Central and East European countries, and was ahead of only two states, Greece and Bulgaria. The level of undeclared work in Romania, Bulgaria, and Greece seems to be related to the high proportion of cash payments.
- (8)
- Elaborating multiannual studies of the shadow economy by carrying out disaggregated analyses by sectors, or types of taxes, aiming at knowing more precisely where, through who, and how the existing fraud occurs.
- (9)
- Developing a functional collaboration between different public administrations: establishing an effective collaboration between the regional and local tax administrations, promoting co-responsibility and the consortium in the fight against tax fraud.
- (10)
- Creating a shared database: the different territorial administrations must share a tax database and the subsidies granted with information from the central, regional, and local spheres.
- (11)
- Improving the efficiency and the speed of the procedures: improve the actions and investigations of the administrations by means of the revision of the procedures and management methods to reduce the duration of the files and the litigation.
- (12)
- Carrying out a better monitoring of risk contributors: the creation of a file of insolvent fiscal debtors (with limitations on the right to obtain subsidies, create companies, occupy positions, and take on public works until they enter or guarantee the debts).
- (13)
- Carrying out fiscal reforms, creating a battery of fiscal measures that help prevent fraud and strengthen the fight against the underground economy.
- (14)
- Revising the taxation of small and medium-sized enterprises (SMEs) and the self-employed to adapt to the economic difficulties of a time of crisis. For this, it is recommended that employers and professionals pay under direct estimation as a general rule, and that the module system is only allowed to micro entrepreneurs who sell exclusively to the final consumer.
- (15)
- Establishing electronic transaction control systems.
- (16)
- Creating an awareness and training plan on the negative effects of the shadow economy.
Author Contributions
Funding
Conflicts of Interest
Appendix A. The Description and Source of the Data
Variables | Unit Root | Description | Sources |
Fiscal regime | I (1) | Total fiscal revenues/GDP, % | Quarterly Government Finance Statistics, Eurostat. |
Direct taxes (X1) | I (1) | Current taxes on income, wealth/GDP, % | Quarterly Government Finance Statistics, Eurostat. |
Indirect taxes (X2) | I (1) | Taxes on production and imports/GDP, % | Quarterly Government Finance Statistics, Eurostat. |
Social contributions (X3) | I (1) | Net social contributions/GDP, % | Quarterly Government Finance Statistics, Eurostat. |
Unemployment rate (X4) | I (1) | ILO unemployment rate, %. | Labour Force Survey, Eurostat. |
Self-employment (X5) | I (1) | Self-employed persons/active pop, % | Labour Force Survey, Eurostat. |
Government consumption (X6) | I (1) | Final consumption expenditure of general government/GDP, %. | Quarterly Government Finance Statistics of Eurostat. |
Part-time employment as a percentage of the total employment (X7) | I (1) | Part-time employment rate, % | Labour Force Survey, Eurostat |
Government employment (X8) | I (1) | Government employment/active pop. %. | Labour Force Survey, Eurostat. |
Regulatory Quality (X9) | I (1) | The scores of this index lie between −2.5 and 2.5, with higher scores corresponding to better outcomes. | Worldwide Governance Indicators, WB |
Government Effectiveness (X9′) | It ranges from approximately −2.5 (weak) to 2.5 (strong) governance performance. | Worldwide Governance Indicators, WB | |
Index of real GDP (2005=100) | I (1) | Chain linked volumes, index 2005=100 | Quarterly National Accounts database of Eurostat. |
C/M1 | I (1) | C/M1, %. It corresponds to the currency outside the banks as a proportion of M1. | Monthly Bulletins of National Bank of Romania |
Labour force participation rate | I (1) | Labour force participation rate, %. | Labour Force Survey, Eurostat. |
Appendix B. The Empirical Results of Mardia Test
Appendix C. The Regional Analysis of the Main Determinants of Shadow Economic Activity
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Authors | Approach | Size of SE (% of Official GDP) |
---|---|---|
Albu [38] Albu et al. [39,40] | Income discrepancy method | 21.7–22.3% (2000) 20.6–21.2% (2001) 20.2–20.7% (2002) 19.3–19.6% (2003) 17.6–17.6% (2004) 17.2–17.3% (2005) 16.3–16.5% (2006) 14.6–15.0% (2007) |
National Institute of Statistics | Labor input method | 18.1% (2000) 15.4% (2003) 16.6% (2005) 20.0% (2007) 21.3% (2009) 23.5% (2010) |
Andrei, Ştefănescu, Oancea [44] | Monetary method | 25–35% (2000–2009) |
Schneider, Buehn and Montenegro [45] Schneider [37,46,47] Medina and Schneider [4] | the MIMIC approach | 34.4% (2000) 30.5% (2005) 26.8% (2010) 29.1% (2012) 24.0% (2013) 28.0% (2015) 27.6% (2016) |
Alexandru and Dobre [41] | Currency demand approach Vector Error Correction Models (VECM) | 36.5% (2000) 34.23% (2003) 33.6% (2005) 32.1% (2008) 31.6% (2010) |
Models | Causes | Indicators | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Tax Burden | Direct Taxes | Indir. Taxes | Social Contr. | Gov. Cons. | Unempl. Rate | Self-Empl. | Gov. Empl. | Reg. Qual. | Govern. Effectiveness | Part-Time Empl. | Real GDP Index | Lab. Force Part. Rate | ||
MIMIC 9-1-3a | - | 0.084 | 0.150 | 0.143 | 0.102 | 1.229 * | 1.003 *** | 0.650 | −4.79 * | 0.086 | −1 | 0.476 * | 0.059 | |
MIMIC 9-1-3b | 0.066 | 0.179 | 0.162 | 0.082 | 1.190 ** | 0.793 * | 0.706 | −5.90 * | 0.135 | −1 | 0.481 * | 0.039 | ||
MIMIC 8-1-3a | - | - | 0.111 | 0.131 | 0.112 | 1.274 * | 0.967 ** | 0.644 | - | −5.11 * | 0.104 | −1 | 0.483 * | 0.052 |
MIMIC 8-1-3b | - | - | 0.149 | 0.152 | 0.088 | 1.223 ** | 0.755 * | 0.687 | −6.18 * | - | 0.155 | −1 | 0.492 * | 0.035 |
MIMIC 7-1-3a | - | - | 0.148 | 0.146 | 0.070 | 1.213 ** | 0.758 * | - | −5.17 * | - | 0.208 * | −1 | 0.588 | 0.080 |
MIMIC 7-1-3b | 0.031 | - | - | - | 0.111 | 1.194 * | 0.820 ** | 0.872 | −5.21 * | 0.166 | −1 | 0.491 * | 0.044 | |
MIMIC 7-1-2a | - | - | 0.172 | 0.245 | - | 1.232 ** | 0.756 * | 0.767 | −7.03 * | - | 0.134 | −1 | 0.443 * | - |
MIMIC 6-1-3a | - | - | 0.114 | 0.141 | - | 1.100 ** | 0.819 ** | - | −4.30 * | - | 0.268 * | −1 | 0.661 * | 0.195 * |
MIMIC 6-1-3b | - | - | 0.016 | 0.069 | - | 0.859 * | 0.876 ** | - | - | −2.62 * | 0.281 * | −1 | 0.606 * | 0.421 * |
MIMIC 5-1-3a | - | - | 0.026 | - | - | 0.743 * | 0.789 * | - | −1.00 * | - | 0.292 * | −1 | 0.710 * | 0.428 ** |
MIMIC 5-1-3b | - | - | 0.008 | - | - | 0.807 * | 0.829 ** | - | - | −2.20 * | 0.285 * | −1 | 0654 * | 0.461 * |
MIMIC 4-1-3a | - | - | - | - | - | 0.668 * | 0.769 ** | - | −0.535 * | - | 0.286 * | −1 | 0.705 * | 0.477 ** |
MIMIC 4-1-3b | - | - | - | - | - | 0.796 * | 0.823 ** | - | - | −2.18 * | 0.285 * | −1 | 0651 * | 0.471 ** |
Global Goodness of Fit Statistics | Chi-square 2 (p-value) | RMSEA 3 (p-value) | CFI | TLI | SRMR | CD | AIC | SBC | ||||||
MIMIC 9-1-3a | 23.22 + (0.182) | 0.06 + (0.197) | 0.577 | 0.294 | 0.062 | 0.364 | 1779.91 | 1941.80 | ||||||
MIMIC 9-1-3b | 24.11 + (0.151) | 0.07 + (0.142) | 0.594 | 0.324 | 0.062 | 0.365 | 1779.80 | 1941.70 | ||||||
MIMIC 8-1-3a | 19.56 + (0.24) | 0.056 + (0.199) | 0.685 | 0.469 | 0.065 | 0.358 | 1572.24 | 1709.40 | ||||||
MIMIC 8-1-3b | 19.80 + (0.229) | 0.058 + (0.17) | 0.713 | 0.516 | 0.066 | 0.367 | 1572.46 | 1709.62 | ||||||
MIMIC 7-1-3a | 16.46 + (0.286) | 0.05 + (0.192) | 0.789 | 0.639 | 0.067 | 0.410 | 1588.06 | 1702.74 | ||||||
MIMIC 7-1-3b | 20.07 + (0.128) | 0.079 + (0.088) | 0.589 | 0.295 | 0.072 | 0.339 | 1424.18 | 1538.85 | ||||||
MIMIC 7-1-2a | 4.34 + (0.63) | 0.00 + (0.822) | 1.00 | 1.382 | 0.028 | 0.316 | 1108.74 | 1216.67 | ||||||
MIMIC 6-1-3a | 12.65 + (0.39) | 0.028 + (0.295) | 0.935 | 0.886 | 0.063 | 0.514 | 1283.88 | 1378.31 | ||||||
MIMIC 6-1-3b | 12.31 + (0.42) | 0.019 + (0.47) | 0.958 | 0.926 | 0.060 | 0.867 | 1283.54 | 1377.98 | ||||||
MIMIC 5-1-3a | 12.15 + (0.275) | 0.055 + (0.275) | 0.794 | 0.629 | 0.065 | 0.778 | 1093.19 | 1169.63 | ||||||
MIMIC 5-1-3b | 10.44 + (0.402) | 0.025 + (0.455) | 0.944 | 0.900 | 0.064 | 0.862 | 1093.11 | 1169.55 | ||||||
MIMIC 4-1-3a | 9.18 + (0.32) | 0.046 + (0.295) | 0.880 | 0.775 | 0.066 | 0.820 | 843.27 | 903.98 | ||||||
MIMIC 4-1-3b | 7.89+ (0.44) | 0.00+ (0.44) | 1.000 | 1.025 | 0.065 | 0.872 | 842.68 | 903.39 |
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Popescu, G.H.; Davidescu, A.A.M.; Huidumac, C. Researching the Main Causes of the Romanian Shadow Economy at the Micro and Macro Levels: Implications for Sustainable Development. Sustainability 2018, 10, 3518. https://doi.org/10.3390/su10103518
Popescu GH, Davidescu AAM, Huidumac C. Researching the Main Causes of the Romanian Shadow Economy at the Micro and Macro Levels: Implications for Sustainable Development. Sustainability. 2018; 10(10):3518. https://doi.org/10.3390/su10103518
Chicago/Turabian StylePopescu, Gheorghe H., Adriana Ana Maria Davidescu, and Catalin Huidumac. 2018. "Researching the Main Causes of the Romanian Shadow Economy at the Micro and Macro Levels: Implications for Sustainable Development" Sustainability 10, no. 10: 3518. https://doi.org/10.3390/su10103518