Abstract
Romania: Selected Issues
Minimum Wage Policy in Romania1
Minimum wages in Romania have risen sharply. Minimum wage increase could have direct effect on wage distribution and improve the income inequality. However, the impact of minimum wage policy on poverty reduction is less clear. Minimum wage hikes may push up overall wages, thus potentially undermining external competitiveness going forward. International experiences suggest the minimum wage fixing should balance social considerations with potential negative impacts from minimum wage hikes.
Core Questions
How is the minimum wage set in Romania?
Why is the minimum wage rising sharply in recent years?
What could be the economic impact from minimum wage increase?
What would be the appropriate minimum wage policy, drawing on international best practices?
A. Minimum Wage Setting in Romania
1. Minimum wage fixing has long been established in Romania to give wage-earners the necessary social protection. The minimum wage in Romania was first introduced in 1949. The level of minimum wage in Romania is determined at national level by the government after consulting the trade unions and employers’ organizations. There is only one minimum wage determined by law. The minimum wage has only one fixed component and is calculated on monthly gross basis. It has typically adjusted twice a year in January and July, except for 2016 in which the minimum wage will be adjusted only once in May. Nonetheless, the main factors underlying the minimum wage adjustments for both macro- and micro-economic factors are not clearly specified. In recent years, the Romanian government has extensively utilized the minimum wage as a tool to achieve the objective set out for Europe strategy 2020 in order to reduce the number of persons at risk of poverty and social exclusion by 580,000 persons.
Minimum Wage
(In lei)
Minimum Wage
(In lei)
| Period | Monthly Minimum Wage |
|---|---|
| 2013-Jan | 700 |
| 2013-Jul | 800 |
| 2014-Jan | 850 |
| 2014-Jul | 900 |
| 2015-Jan | 975 |
| 2015-Jul | 1050 |
| 2016-May | 1250 |
Minimum Wage
(In lei)
| Period | Monthly Minimum Wage |
|---|---|
| 2013-Jan | 700 |
| 2013-Jul | 800 |
| 2014-Jan | 850 |
| 2014-Jul | 900 |
| 2015-Jan | 975 |
| 2015-Jul | 1050 |
| 2016-May | 1250 |
2. Minimum wages in Romania has risen sharply. Minimum wages will be raised again in May 2016, reflecting about 78.6 percent increase from end-2012. With the planned increase in 2016, the minimum wage in Romania would leap to approximately 45.3 percent of mean wage and 65.4 percent of median wage which is high by international standards. In 2013, there were approximately 430 thousand workers in Romania with wages at or below the minimum wage, accounting for about 11.2 percent of total registered workers. Minimum wage workers are largely concentrated in construction, trade, manufacturing, hotels and restaurants. The majority of these workers are among working-age group and about two-thirds of minimum wage workers are male. There were only 0.5 percent of government employees who received minimum wage in 2013, and a large increase in public sector wage in 2016 would lift the monthly salary for all government employees above the minimum wage.
Share of Minimum Wage Earners (%)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Sources: INSSE, EurostatShare of Minimum Wage Earners (%)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Sources: INSSE, EurostatShare of Minimum Wage Earners (%)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Sources: INSSE, Eurostat
Minimum Wage Earners by Sector
(Workers at or below minimum wage in percent of total workers in each sector, data as of 2013)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Sources: INSSE, IMF staff calculationsMinimum Wage Earners by Sector
(Workers at or below minimum wage in percent of total workers in each sector, data as of 2013)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Sources: INSSE, IMF staff calculationsMinimum Wage Earners by Sector
(Workers at or below minimum wage in percent of total workers in each sector, data as of 2013)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Sources: INSSE, IMF staff calculationsB. Minimum Wage Developments and Its Interactions with Relevant Macroeconomic Variables
3. Minimum wage increases in Romania are among one of the steepest among European peers since 2005. Although the minimum wage in national currency and euros remain low, the speed of the increase in minimum wage in both nominal and real terms for Romania is far greater than EU peers. Minimum relative to average wage ratio for Romania had always been among the low-end group, but will likely top the regional average with the planned increase in 2016.
Monthly Minimum Wage 1/
(2005.Q1 = 100) 300
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Sources: Eurostat Haver, IMF staff calculations1/ Data are in real term. Nominal monthly minimum wages are deflated by consumer priceindices.Monthly Minimum Wage 1/
(2005.Q1 = 100) 300
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Sources: Eurostat Haver, IMF staff calculations1/ Data are in real term. Nominal monthly minimum wages are deflated by consumer priceindices.Monthly Minimum Wage 1/
(2005.Q1 = 100) 300
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Sources: Eurostat Haver, IMF staff calculations1/ Data are in real term. Nominal monthly minimum wages are deflated by consumer priceindices.
Minimum Wage to Average Wage Ratio in CESEE
(Percent)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Sources: Eurostat, National Authority, IMF Staff Projections1/ 2015 dataMinimum Wage to Average Wage Ratio in CESEE
(Percent)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Sources: Eurostat, National Authority, IMF Staff Projections1/ 2015 dataMinimum Wage to Average Wage Ratio in CESEE
(Percent)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Sources: Eurostat, National Authority, IMF Staff Projections1/ 2015 data4. Minimum wage policy might have helped to reduce income inequality in Romania, whereas the poverty risk declined only slightly. During 2006–14, minimum relative to average wage rose by about 8 percent, and the Gini coefficients declined by around 2.8 percent. A simple correlation between the minimum to average wage ratios and Gini coefficient at the same period was negative and particularly strong for Romania. The income gaps measured by the ratio between the highest and the lowest income deciles also reduced from 14.7 times in 2006 to 13.4 times in 2014. Nevertheless, the poverty rate declined only slightly with the minimum wage increases during 2006–14 and the two appeared to be uncorrelated.
Minimum Wage and Gini Coefficient
(change from 2006 to 2014)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Sources: Eurostat, IMF staff calculationsMinimum Wage and Gini Coefficient
(change from 2006 to 2014)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Sources: Eurostat, IMF staff calculationsMinimum Wage and Gini Coefficient
(change from 2006 to 2014)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Sources: Eurostat, IMF staff calculations
Minimum Wage and Poverty Rate
(change from 2006 to 2014)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Sources: Eurostat, IMF staff calculationsMinimum Wage and Poverty Rate
(change from 2006 to 2014)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Sources: Eurostat, IMF staff calculationsMinimum Wage and Poverty Rate
(change from 2006 to 2014)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Sources: Eurostat, IMF staff calculations5. Minimum wage hikes may pass through overall wages and push labor costs. Minimum wage increases, if binding, would raise the wages paid to minimum wage workers. Moreover, workers receiving wages above the minimum wage level may negotiate for their wage increases, anchoring from the announced minimum wage hikes and any resulting inflation rises to maintain their purchasing power. At a glance, minimum wage growth and average gross wage growth appeared to be positively correlated among European countries. Furthermore, the evidences from firm-level surveys under the Wage Dynamic Network (WDN) of European System of Central Banks (ESCB) show that around a fifth of firms in the survey had to increase the wages of employees earning above the minimum wage level along with the minimum wage rises.2 In Romania, minimum wage increases in January and July 2014 and January 2015 would directly contribute to the month-on-month growth of the average gross wage in private sector by about 0.5 percent (NBR, 2015). Nevertheless, minimum wage increases do not seem to match with labor productivity growth.
Minimum wage and gross wages
(Percent annual change avg 2001-2013 for 19 EU countries)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Sources: Eurostat, IMF staff calculationsMinimum wage and gross wages
(Percent annual change avg 2001-2013 for 19 EU countries)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Sources: Eurostat, IMF staff calculationsMinimum wage and gross wages
(Percent annual change avg 2001-2013 for 19 EU countries)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Sources: Eurostat, IMF staff calculations
Minimum wage to average productivity ratio
(percent)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Minimum wage to average productivity ratio
(percent)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Minimum wage to average productivity ratio
(percent)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
6. Romania’s labor market was insulated from minimum wage hikes so far. At the aggregate level, labor force participation increased gradually. Employment grew across the board. Despite relatively large share of minimum wage workers, the employment in trade service and hotels and restaurants expanded. The employment in construction sector declined in 2013, but recovered swiftly in 2014. The full-time employment was held up well, but the part-time employment continued to decline. Such benign impacts of minimum wage hikes on the employment in Romania may be due to the fact that minimum wage hikes emerged from low wage base and growing economy in recent years had helped to absorb the negative impact on employment. In addition, firms might choose to cut down their margins or reduce non-labor costs and rather to maintain jobs.
Labor Force Participation
(Percent of working age population)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Sources: INSSE, Eurostat, IMF Staff CalculationsLabor Force Participation
(Percent of working age population)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Sources: INSSE, Eurostat, IMF Staff CalculationsLabor Force Participation
(Percent of working age population)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Sources: INSSE, Eurostat, IMF Staff Calculations
Employment
(Percent change)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Employment
(Percent change)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Employment
(Percent change)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Employment
(Percent change)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Employment
(Percent change)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Employment
(Percent change)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
C. Economic Impacts of Minimum Wage Increases
7. The increase in minimum wage could improve economic equality but may also have potential negative impacts. The Romanian government introduced the active minimum wage policy as part of measures to tackle poverty. On the upside, minimum wage increases may help to reduce wage gaps and improve income inequality. The minimum wage increase and its ripple effect across wage distribution will give boost to short-term consumer spending. Minimum wage increase may incentivize low-paid workers to work in the formal sector, but this impact is not obvious as at the same time it may give rise to envelope pay to circumvent the minimum wage increase. On the other hand, minimum wage hikes could push average gross wages and labor costs. Increased wages and labor costs could undermine external competitiveness and export performance, while hampering potential foreign direct investment that could benefit low skilled labor. Minimum wage is, in principle, a wage floor. If the floor is set too high, it could affect firms’ profitability and discourage employers from hiring, particularly among directly affected group. Should the employment effect be intensified, the increase in unemployment may affect family income among low-paid group and in turn lowered income would have the repercussion effect on the poverty level. The following sections analyze the economic impacts of minimum wage increases in Romania in more details.
Arguments For and Against Minimum Wage Increase
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Arguments For and Against Minimum Wage Increase
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Arguments For and Against Minimum Wage Increase
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Wage and Income Distribution
8. Minimum wage increase could have direct effect on wage distribution and narrow wage gaps between high and low pays. From the analysis of Romania’s wage distribution (Appendix I), the increases in minimum wages immediately raised the employment income of the bottom part of the wage distribution and increased the coverage of minimum wage earners.3 Median wage income was rising. The wage distribution became less positively skewed overtime. The kurtosis of the wage distribution also went down, reflecting less heavy tailed or less outliers both at the bottom and top of the distribution. In line with NBR (2015), the wage income distribution would likely squeeze around the minimum threshold with the minimum wage hikes toward the planned increase in 2016. The cumulative distribution of annual wages shifted to the right with greater frequency centered at the middle of the distribution. The ratio of the top and bottom income percentiles declined significantly from 21.2 times in 2007 to around 15.6 times in 2014, and would likely fall to around 13.1 times by 2016.
Cumulative Distribution of Annual Wages
(Real annual wage in Lei, each dot presents minimum wage for each year)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Sources: EU-SILC, INSSE, IMF staff calculationsCumulative Distribution of Annual Wages
(Real annual wage in Lei, each dot presents minimum wage for each year)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Sources: EU-SILC, INSSE, IMF staff calculationsCumulative Distribution of Annual Wages
(Real annual wage in Lei, each dot presents minimum wage for each year)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Sources: EU-SILC, INSSE, IMF staff calculations
Wage Distribution in 2007
(Annual wage income of paid employed persons)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Wage Distribution in 2007
(Annual wage income of paid employed persons)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Wage Distribution in 2007
(Annual wage income of paid employed persons)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Wage Distribution in 2010
(Annual wage income of paid employed persons)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Wage Distribution in 2010
(Annual wage income of paid employed persons)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Wage Distribution in 2010
(Annual wage income of paid employed persons)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Wage Distribution in 2014
(Annual wage income of paid employed persons)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Sources: EU-SILC, INSSE, IMF staff calculationsWage Distribution in 2014
(Annual wage income of paid employed persons)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Sources: EU-SILC, INSSE, IMF staff calculationsWage Distribution in 2014
(Annual wage income of paid employed persons)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Sources: EU-SILC, INSSE, IMF staff calculations
Wage Distribution in 2016 projection
(Annual wage income of paid employed persons)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Wage Distribution in 2016 projection
(Annual wage income of paid employed persons)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Wage Distribution in 2016 projection
(Annual wage income of paid employed persons)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
9. The effectiveness of the minimum wage policy on wage distribution could be largely exhausted with persistently sharp hikes of minimum wage. The minimum wage rises appeared to have strong re-distributional impact on the wage distribution during 2009 to 2012 as the wage distribution winded down towards a more equally distributed pattern. The more recent minimum wage hikes during 2013–16 would have lifted the wage profiles at all levels, but barely changed the wage distribution. The wage gaps between the top and bottom income percentiles have widened somewhat in 2013 and 2014, and would then narrow to around 12 times by 2016. Since the analysis has not controlled for other factors affecting the distribution of wage, this may be the evidence of minimum wages playing a rather moderate role compared to everything else during the period.
Minimum-to-Average Wage Ratio and Wage Gaps 1/
(Percent)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Sources: Eurostat, INSSE, IMF Staff Calculations1/ Wage gap is defined as the ratio of top-to-bottom wage income decliesMinimum-to-Average Wage Ratio and Wage Gaps 1/
(Percent)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Sources: Eurostat, INSSE, IMF Staff Calculations1/ Wage gap is defined as the ratio of top-to-bottom wage income decliesMinimum-to-Average Wage Ratio and Wage Gaps 1/
(Percent)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Sources: Eurostat, INSSE, IMF Staff Calculations1/ Wage gap is defined as the ratio of top-to-bottom wage income declies10. Minimum wage increases could also contribute to improve income inequality. The improvement in wage distribution resulted from minimum wage rises would likely drive the change in income distribution, given that employed persons represent the largest proportion in total population and wages are considered a major source of income. In Romania, the paid employed persons in the household survey accounts for about 43.6 percent of total surveyed persons, comparing to around a third of total labor forces at the aggregate level. Likewise, wage income accounts for about 60 percent of total personal income in the survey. In fact, the redistribution of wages in Romania had helped to reduce income inequality in terms of both improved median income and income gaps, particularly over the period of 2008–11. However, it is important to note that despite potential benefit of the minimum wage policy on income inequality, the wage distribution and income distribution remains very different and much of the population is not on the formal employment payrolls. In particular, the link between minimum wages and income inequality could be weak because the truly poor might not work at all such as unemployed persons and pensioners while many minimum wage earners may live in not-so-poor households. To fully address the income inequality and reduce the poverty, other policy instruments may be required (Table 2).
Wage and Income Distribution
(In lei, unless otherwise indicated)
Wage and Income Distribution
(In lei, unless otherwise indicated)
| 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | |||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Proj. | Proj. | |||||||||||
| MW annual income | 4,680 | 6,000 | 7,200 | 7,200 | 8,040 | 8,400 | 9,000 | 10,500 | 12,150 | 14,200 | ||
| %change | 18.2 | 28.2 | 20.0 | 0.0 | 11.7 | 4.5 | 7.1 | 16.7 | 15.7 | 16.9 | ||
| Gross wage annual | 16,916 | 20,906 | 22,672 | 23,240 | 24,383 | 25,606 | 26,890 | 28,320 | 30,714 | 33,601 | ||
| %change | 22.6 | 23.6 | 8.4 | 2.5 | 4.9 | 5.0 | 5.0 | 5.3 | 8.5 | 9.4 | ||
| Paid workers at or under MW (persons) | 2,276 | 2,139 | 2,066 | 1,970 | 2,024 | 2,041 | 2,218 | 2,409 | 2,659 | 3,161 | ||
| Paid workers (persons) | 7,906 | 7,339 | 7,207 | 7,154 | 6,920 | 6,841 | 6,932 | 6,836 | 6,836 | 6,836 | ||
| Share of MW paid workers (in percent) | 28.8 | 29.1 | 28.7 | 27.5 | 29.2 | 29.8 | 32.0 | 35.2 | 38.9 | 46.2 | ||
| Distribution of Annual Wage | ||||||||||||
| Median annual wage | 8,013 | 9,349 | 10,997 | 11,726 | 12,081 | 12,130 | 12,432 | 13,233 | 14,065 | 15,014 | ||
| % change | 17 | 18 | 7 | 3 | 0 | 2 | 6 | 6 | 7 | |||
| Skewness (0 = normal) | 3 | 5 | 11 | 8 | 4 | 2 | 2 | 2 | 2 | 2 | ||
| Kurtosis (3 = normal) | 23 | 109 | 403 | 226 | 76 | 18 | 18 | 14 | 15 | 15 | ||
| 10th percentile | 900 | 1,400 | 1,650 | 1,500 | 1,600 | 1,800 | 1,750 | 1,743 | 2,016 | 2,357 | ||
| 90th percentile | 19,101 | 21,347 | 24,188 | 24,387 | 24,199 | 24,462 | 25,146 | 27,226 | 28,937 | 30,890 | ||
| Wage gap (top-to-bottom income) | 21 | 15 | 15 | 16 | 15 | 14 | 14 | 16 | 14 | 13 | ||
| Distribution of Gross Annual Income | ||||||||||||
| Median gross annual income | 4,200 | 5,317 | 6,765 | 7,736 | 8,200 | 8,371 | 8,400 | 8,798 | … | … | ||
| Skewness (0=normal) | 4.2 | 5.8 | 9.8 | 6.7 | 3.8 | 2.7 | 34.4 | 44.3 | … | … | ||
| Kurtosis (3=normal) | 42.5 | 111.4 | 374.5 | 195.1 | 64.7 | 29.3 | 2598.7 | 2955.4 | … | … | ||
| 10th percentile | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | … | … | ||
| 20th percentile | 490 | 630 | 976 | 1116 | 1180 | 910 | 791 | 950 | … | … | ||
| 90th percentile | 14072 | 15295 | 17797 | 19248 | 19134 | 19559 | 20292 | 22005 | … | … | ||
| Income gap (90th to 20th income percentiles | 28.7 | 24.3 | 18.2 | 17.2 | 16.2 | 21.5 | 25.6 | 23.2 | … | … | ||
Wage and Income Distribution
(In lei, unless otherwise indicated)
| 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | |||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Proj. | Proj. | |||||||||||
| MW annual income | 4,680 | 6,000 | 7,200 | 7,200 | 8,040 | 8,400 | 9,000 | 10,500 | 12,150 | 14,200 | ||
| %change | 18.2 | 28.2 | 20.0 | 0.0 | 11.7 | 4.5 | 7.1 | 16.7 | 15.7 | 16.9 | ||
| Gross wage annual | 16,916 | 20,906 | 22,672 | 23,240 | 24,383 | 25,606 | 26,890 | 28,320 | 30,714 | 33,601 | ||
| %change | 22.6 | 23.6 | 8.4 | 2.5 | 4.9 | 5.0 | 5.0 | 5.3 | 8.5 | 9.4 | ||
| Paid workers at or under MW (persons) | 2,276 | 2,139 | 2,066 | 1,970 | 2,024 | 2,041 | 2,218 | 2,409 | 2,659 | 3,161 | ||
| Paid workers (persons) | 7,906 | 7,339 | 7,207 | 7,154 | 6,920 | 6,841 | 6,932 | 6,836 | 6,836 | 6,836 | ||
| Share of MW paid workers (in percent) | 28.8 | 29.1 | 28.7 | 27.5 | 29.2 | 29.8 | 32.0 | 35.2 | 38.9 | 46.2 | ||
| Distribution of Annual Wage | ||||||||||||
| Median annual wage | 8,013 | 9,349 | 10,997 | 11,726 | 12,081 | 12,130 | 12,432 | 13,233 | 14,065 | 15,014 | ||
| % change | 17 | 18 | 7 | 3 | 0 | 2 | 6 | 6 | 7 | |||
| Skewness (0 = normal) | 3 | 5 | 11 | 8 | 4 | 2 | 2 | 2 | 2 | 2 | ||
| Kurtosis (3 = normal) | 23 | 109 | 403 | 226 | 76 | 18 | 18 | 14 | 15 | 15 | ||
| 10th percentile | 900 | 1,400 | 1,650 | 1,500 | 1,600 | 1,800 | 1,750 | 1,743 | 2,016 | 2,357 | ||
| 90th percentile | 19,101 | 21,347 | 24,188 | 24,387 | 24,199 | 24,462 | 25,146 | 27,226 | 28,937 | 30,890 | ||
| Wage gap (top-to-bottom income) | 21 | 15 | 15 | 16 | 15 | 14 | 14 | 16 | 14 | 13 | ||
| Distribution of Gross Annual Income | ||||||||||||
| Median gross annual income | 4,200 | 5,317 | 6,765 | 7,736 | 8,200 | 8,371 | 8,400 | 8,798 | … | … | ||
| Skewness (0=normal) | 4.2 | 5.8 | 9.8 | 6.7 | 3.8 | 2.7 | 34.4 | 44.3 | … | … | ||
| Kurtosis (3=normal) | 42.5 | 111.4 | 374.5 | 195.1 | 64.7 | 29.3 | 2598.7 | 2955.4 | … | … | ||
| 10th percentile | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | … | … | ||
| 20th percentile | 490 | 630 | 976 | 1116 | 1180 | 910 | 791 | 950 | … | … | ||
| 90th percentile | 14072 | 15295 | 17797 | 19248 | 19134 | 19559 | 20292 | 22005 | … | … | ||
| Income gap (90th to 20th income percentiles | 28.7 | 24.3 | 18.2 | 17.2 | 16.2 | 21.5 | 25.6 | 23.2 | … | … | ||
Wage vs Income Distribution
(Annual wage and gross income in Lei, data in 2014)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Sources: EU-SILC, IMF Staff CalcuationsWage vs Income Distribution
(Annual wage and gross income in Lei, data in 2014)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Sources: EU-SILC, IMF Staff CalcuationsWage vs Income Distribution
(Annual wage and gross income in Lei, data in 2014)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Sources: EU-SILC, IMF Staff Calcuations11. The impact of minimum wage policy on poverty reduction is less clear. Since the risk of poverty is higher among the low paid, reducing the number of low-paid workers may help to reduce working poverty. On Romania, the risk of in-work poverty or social exclusion slightly declined as minimum wages increased. Nevertheless, the causality of the minimum wage as policy instrument to reduce poverty would require more granular data analysis to pin down the effect. In fact, the empirical findings in the area are found controversial. CBO (2014) found the income of families whose income is below or close to the poverty threshold would rise significantly, while the income of richer families would decrease. Yet, Neumark and others (2005) mentioned that an increase in minimum wage raised the incomes of some poor families, but minimum wages appeared to increase the proportion of families that are poor or nearly poor due to the disemployment effect. Further to this, IMF (2014) and Neumark (2015) noted a large share of the higher income from minimum wages flows to higher-income families as minimum wages rise. Such findings point to the efficiency and equity concerns of minimum wage policy.
Pass-Through of Minimum Wage on Average Wage
12. Minimum wage policies can affect gross wages through the wage redistribution and play a signaling role at the economy-wide wage setting. This study utilizes the panel VARs technique to estimate the reduced-form wage-setting system.4 The dynamics of such pass-through can be characterized by the resulting impulse response of minimum wage increase on average gross wage growth. The pass-through is estimated at about 0.01–0.15 percent increase in real average wage growth in response to 1 percent increase in real minimum wage over two years. The result indicates a minimum wage shock could have a significant and long-lasting effect on the overall wage growth. One explanation is that during 2011–16, several CESE countries have actively used the minimum wage policy, and the minimum relative to average wage ratios in many CESE countries rose remarkably to 45–50 percent from mid-30 percent range in the past decade. The share of minimum wage earners may have increased significantly. Therefore, minimum wage hikes could potentially blow stronger ripple effects across the wage distribution above minimum wage.
Minimum Wage Pass-Through
(The response of average wage to 1 ppt increase in minimum wage, panel VAR model for 14 CESE countries during 2010q1-2015q2)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Source: IMF staff estimatesMinimum Wage Pass-Through
(The response of average wage to 1 ppt increase in minimum wage, panel VAR model for 14 CESE countries during 2010q1-2015q2)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Source: IMF staff estimatesMinimum Wage Pass-Through
(The response of average wage to 1 ppt increase in minimum wage, panel VAR model for 14 CESE countries during 2010q1-2015q2)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Source: IMF staff estimates
Minimum Wage Pass-Through
(The response of average wage to 1ppt increase in minimum wage, country level VAR estimate)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Source: IMF Staff EstimatesMinimum Wage Pass-Through
(The response of average wage to 1ppt increase in minimum wage, country level VAR estimate)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Source: IMF Staff EstimatesMinimum Wage Pass-Through
(The response of average wage to 1ppt increase in minimum wage, country level VAR estimate)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Source: IMF Staff Estimates13. Supporting evidences from Romania-specific estimates emphasize the role of minimum wage as an important push factor for the overall wage growth. To further identify the impact of minimum wage hikes on overall wages, this study explores a more granular pass-through effect at country and sectoral level.5 The pass-through estimated at the country level for Romania range from 0.45 to 0.55 percent increase in average gross wage in response to 1 percent increase in minimum wage, but the significant level is low. Potentially stronger pass-through of minimum wage of a particular country or sector may be resulted from the level of minimum wage coverage and a large share of minimum wage workers within the country or sector being considered. Having said that, some firms may offset higher minimum wages by lowering non-wage benefits, hours, or under-the-table wage supplements (IMF, 2016). Therefore, the effect of minimum wages on remuneration may not be obvious.
Minimum Wage Pass-Through, Industry
(The response of average wage to 1ppt increase in MW)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Minimum Wage Pass-Through, Industry
(The response of average wage to 1ppt increase in MW)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Minimum Wage Pass-Through, Industry
(The response of average wage to 1ppt increase in MW)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Minimum Wage Pass-Through, Services
(The response of average wage to 1ppt increase in MW)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Minimum Wage Pass-Through, Services
(The response of average wage to 1ppt increase in MW)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Minimum Wage Pass-Through, Services
(The response of average wage to 1ppt increase in MW)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Minimum Wage Pass-Through, IT
(The response of average wage to 1ppt increase in MW)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Source: IMF Staff EstimatesMinimum Wage Pass-Through, IT
(The response of average wage to 1ppt increase in MW)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Source: IMF Staff EstimatesMinimum Wage Pass-Through, IT
(The response of average wage to 1ppt increase in MW)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Source: IMF Staff Estimates
Minimum Wage Pass-Through, Construction
(The response of average wage to 1ppt increase in MW)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Minimum Wage Pass-Through, Construction
(The response of average wage to 1ppt increase in MW)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Minimum Wage Pass-Through, Construction
(The response of average wage to 1ppt increase in MW)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Employment
14. Existing literatures find the impact of minimum wage on employment appears to be modest. Neumark, Schweitzer, and Wascher (2000) estimate the disemployment effects for those at the minimum and those just above the minimum wage of around 0.12 to 0.17 percent in response to 1 percent increase in minimum wage in the U.S. Focusing on the evidences from CESE countries, studies find relatively strong disemployment effect for workers who earned minimum wage but less so at the aggregate level. Hinnosaar and Room (2003) find the minimum wage increase in Estonia has a negative but modest effect on the employment of those workers directly affected by minimum wage change, or about 0.43–0.66 percent reduction in employment in response to 10 percent increase in minimum wage. Baranowska-Rataj and Magda (2015) find a large impact on job separations among workers directly affected by the minimum wage increase in Poland, especially among temporary and young workers. Kertesi and Kollo (2003) find substantial employment losses with sharp minimum wage hikes of about 57 percent in Hungary during 2000–01 of which small-firm employment were most affected. In addition, Andreica and others (2010) estimated the real minimum wage increase of 10 percent can have a significant negative effect on employment of about 0.9 percent over one year for Romania.
Minimum Wage and Employment 1/
(Percent annual change avg. 2001-2013 for 19 EU countries)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Source: Eurostat, IMF Staff Calculations1/ Chart presents simple correlation between minimum wage and employment that may not imply causality.Minimum Wage and Employment 1/
(Percent annual change avg. 2001-2013 for 19 EU countries)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Source: Eurostat, IMF Staff Calculations1/ Chart presents simple correlation between minimum wage and employment that may not imply causality.Minimum Wage and Employment 1/
(Percent annual change avg. 2001-2013 for 19 EU countries)
Citation: IMF Staff Country Reports 2016, 114; 10.5089/9781475555370.002.A003
Source: Eurostat, IMF Staff Calculations1/ Chart presents simple correlation between minimum wage and employment that may not imply causality.15. Nonetheless, some negative impacts on employment of youth and low-skilled could be expected, particularly in countries with high relative minimum wage. Staff’s analysis (IMF, 2016) illustrates the employment impact of minimum wage increases on youth employment at different levels of minimum-to-average wage ratios for 17 CESE countries using data from 2000 to 2014. The study finds that some negative employment effects start to materialize when minimum to average wage ratio exceeds 40 percent. The effects could potentially enlarge toward higher minimum-to-average wage ratios, reflecting its non-linearity nature. In addition, staff’s estimates based on firm-level data for eight CESE countries indicate the increase in minimum wage would result in a decrease in firms’ employment, particularly among firms in tradable sector.
Competitiveness
16. Sharp minimum wage hikes could undermine external competitiveness. High level of minimum wage that passes on to overall wages and labor costs would deteriorate the country’s competitiveness, especially when wage growth is already outstripping productivity growth. Export performance could be jeopardized (Rahman and others, 2015, see Appendix II). Specifically, the estimates suggest the value-added exports of goods and services particularly to EU will likely decline by 0.083 percent for 1 percent increase in minimum relative to average wage ratio. Rising labor costs may also deter foreign direct investment which otherwise would have created jobs. Furthermore, sharp and sudden increases in minimum wage could affect firms’ profitability particularly for firms in tradable sector. For the period of 2009–13, when minimum wage increases were smaller, firm-level analysis reveals that tradable sector firms appear to absorb higher labor costs. They experience somewhat lower profits and employment growth, as they restrain to increase prices and lose competitiveness. However, the impact of the currently larger increases of minimum wage are uncertain and worth monitoring (IMF, 2016).
D. Minimum Wage Policy: International Experiences and Policy Recommendations
17. International experiences suggest the minimum wage fixing should balance social considerations with potential negative impacts from minimum wage hikes. The International Labor Organization (ILO) convention on minimum wage fixing (1970) suggests several elements to be taken into consideration in determining the level of minimum wages: (a) the needs of workers and their families; and (b) economic factors including the requirements of economic development, levels of productivity and the desirability of attaining and maintaining a high level of employment. To tackle poverty in particular, minimum wages may need to be combined with other policies to be effective.
18. Future decisions on minimum wage need to be carefully crafted. The pace of future minimum wage increases should be moderate and balance social considerations with competitiveness, productivity growth, and employment prospects. As minimum-to-average wage ratios in Romania are already higher than in peers, the economic effects could weigh on Romania’s perceived competitiveness in the region. Hence, future minimum wage adjustments could usefully be based on a transparent and clear mechanism and avoid unsustainably rapid increases to shun adverse effects. Minimum wage in Romania is determined at the national level by the government after consulting trade unions and employers’ organizations. It is important to ensure sufficient representation from many low-wage sectors representing the interest of the group affected by the minimum wage. Finally, periodic assessments of the impact of labor market policy including minimum wages by labor market expert committees could usefully inform future policy decisions.
Key Recommendations on Minimum Wage Policy
Key Recommendations on Minimum Wage Policy
| References | Key recommendations |
|---|---|
| G20 joint report by the ILO, OCED, IMF, and the World Bank 2012 | Maintaining the purchasing power of minimum wages at around 30 to 40 percent of median wages sustains demand and reduces poverty and income inequalities. |
| Council of Europe | The Council’s European Committee of Social Rights (ECSR) has put forward a definition according to which a “fair” or “decent” wage is at least 60 percent of the average net wage and certainly not below a level of 50 percent of the average net wage. |
| OECD Employment Outlook 2015 | Minimum wages are relatively blunt tool for tackling poverty even in the absence of any negative effect on employment. Minimum wage, therefore, needs to be combined with other policies to be effective. |
| IMF country report on Germany No.14/216 | The new nationwide minimum wage will help reduce growing wage inequality, but risks exacerbating unemployment in some regions. Decisions on the future level of the minimum wage should take the employment effects into account. |
| IMF country report on the United States No.14/221 | On its own, a minimum wage hike can be a poorly targeted instrument to reduce poverty. Improved employment prospects and economic growth will be essential to reverse a jump in the number of families living poverty. An expansion of the Earned Income Tax Credit and an increase in the minimum wage should also be part of the solution. |
| IMF country report on Republic of Estonia No.15/336 | Competitiveness could come under pressure from wage growth, which has outstripped productivity gains in recent years. There is a need to cool wage growth, including through moderation in public sector wage policy and ensuring that unsustainably rapid minimum wage growth does not set the pace for general wage developments. |
Key Recommendations on Minimum Wage Policy
| References | Key recommendations |
|---|---|
| G20 joint report by the ILO, OCED, IMF, and the World Bank 2012 | Maintaining the purchasing power of minimum wages at around 30 to 40 percent of median wages sustains demand and reduces poverty and income inequalities. |
| Council of Europe | The Council’s European Committee of Social Rights (ECSR) has put forward a definition according to which a “fair” or “decent” wage is at least 60 percent of the average net wage and certainly not below a level of 50 percent of the average net wage. |
| OECD Employment Outlook 2015 | Minimum wages are relatively blunt tool for tackling poverty even in the absence of any negative effect on employment. Minimum wage, therefore, needs to be combined with other policies to be effective. |
| IMF country report on Germany No.14/216 | The new nationwide minimum wage will help reduce growing wage inequality, but risks exacerbating unemployment in some regions. Decisions on the future level of the minimum wage should take the employment effects into account. |
| IMF country report on the United States No.14/221 | On its own, a minimum wage hike can be a poorly targeted instrument to reduce poverty. Improved employment prospects and economic growth will be essential to reverse a jump in the number of families living poverty. An expansion of the Earned Income Tax Credit and an increase in the minimum wage should also be part of the solution. |
| IMF country report on Republic of Estonia No.15/336 | Competitiveness could come under pressure from wage growth, which has outstripped productivity gains in recent years. There is a need to cool wage growth, including through moderation in public sector wage policy and ensuring that unsustainably rapid minimum wage growth does not set the pace for general wage developments. |
Appendix I. Wage and Income Distribution
This study utilizes the micro-level data from EU-SILC for Romania to analyze how the minimum wage impacts the wage distribution and how effective the minimum wage is as the instrument to improve wage and income inequality. The analysis follows the methodology as in Maloney and Mendez (2004) and the United States’ Congressional Budget Office (2014).
The EU-SILC is the EU reference source for comparative statistics on income distribution and social exclusion at the European level. The Romania’s EU-SILC data are provided through the National Institute of Statistics of Romania (INSSE). This study focuses on the developments of wage distribution or gross employment income of paid employed persons.1 The data are both cross-sectional and longitudinal, produced annually from 2007 to 2014. In 2014, for example, there were 7,508 households or 15,661 persons interviewed in the survey (text chart). Of which, 2,499 persons are unemployed and 13,162 persons are either employees or self-employed. The study focuses only on paid employed persons of 6,836 persons accounting for about 43.6 percent of total surveyed persons in 2014.
The wage distributional data for 2015 and 2016 are projected to capture the impacts of sharp minimum wage hikes in recent years. Specifically, sub-minimum wage workers would receive the wage hikes at the growth rate of minimum wage, workers at minimum wage would immediately be paid at the new minimum wage, and workers above minimum wage would receive the pay rise taking into account the pass-through of the growth rate of minimum wage.2
Appendix II. The Impact of Minimum Wage on Export Performance
Rahman and others (2015) analyzes the determinants of value-added exports of goods and services to EU for 10 New Member States (NMS). They point to the importance of structural reforms, particularly in the areas of higher education, skills upgrade, wage structure’s ability to provide incentives to work and foreign investment environment. Of which, the relative minimum wage defined as the minimum wage in percent of average gross wages is identified to have a significant negative impact on export performance. The estimates suggest the value-added exports of goods and services will likely decline by 0.047 percent for 1 percent increase in minimum relative to average wage ratio.
Determinants of Export Performance in NMS
Determinants of Export Performance in NMS
| (1) Value Added exports to EU: goods and services | (2) Value Added exports to the world: goods and services | (3) Gross exports to EU (GE) | (4) Value Added exports to EU: goods | (5) Value Added Exports to EU: services | (6) GE to EU: goods | (7) GE to EU: services | (8) Value Added exports to EU: advanced EU | |
|---|---|---|---|---|---|---|---|---|
| Upper secondary or tertiary educational attainment | 0.156* | 0.301*** | 0.417*** | 0.147*** | 0.023 | 0.415*** | 0.002 | 0.036 |
| Participation in continuous vocational training and skills upgrade | (0.083) | (0.099) | (0.156) | (0.040) | (0.034) | (0.128) | (0.050) | (0.042) |
| 0.147*** | 0.035 | 0.310*** | 0.107*** | 0.049*** | 0.259*** | 0.051*** | −0.005 | |
| (0.029) | (0.035) | (0.053) | (0.014) | (0.012) | (0.044) | (0.017) | (0.064) | |
| Inactivity trap | −0.0917*** | −0.032 | −0.195*** | −0.055*** | −0.029** | −0.155*** | −0.040** | 0.263*** |
| (0.026) | (0.032) | (0.051) | (0.013) | (0.011) | (0.042) | (0.017) | (0.052) | |
| Relative minimum wage | −0.083** | −0.047 | −0.369*** | −0.135*** | −0.004 | −0.369*** | 0.000 | −0.221*** |
| (0.038) | (0.045) | (0.061) | (0.016) | (0.013) | (0.050) | (0.020) | (0.033) | |
| Foreign investment and ownership environment | 0.905** | 0.998* | 2.961*** | 0.749*** | 0.492*** | 2.487*** | 0.474* | 1.804*** |
| (0.424) | (0.507) | (0.752) | (0.195) | (0.165) | (0.617) | (0.243) | (0.494) | |
| Share of exports processed by supply chain | 0.450*** | 0.571*** | 1.217*** | 0.136*** | 0.208*** | 0.904*** | 0.313*** | 0.259** |
| (0.118) | (0.141) | (0.186) | (0.048) | (0.041) | (0.152) | (0.060) | (0.085) | |
| Real effective exchange rate (ULC based) | −0.030 | −0.023 | −0.064 | |||||
| (0.019) | (0.022) | −0.087 | ||||||
| Weighted real GDP growth of trading partners | 0.055 | 0.162** | −0.082 | |||||
| (0.060) | (0.072) | −0.119 | ||||||
| Population | 0.475 | 1.327** | −0.622* | |||||
| (0.551) | (0.659) | −0.333 | ||||||
| PPP GDP per capita | 0.000 | 0.0003*** | ||||||
| (0.000) | (0.0001) | |||||||
| GDP weighted distance | 0.000 | −0.0009** | ||||||
| (0.000) | (0.0003) | |||||||
| Constant | −29.265*** | −45.783*** | −96.763*** | −10.829** | −13.305*** | −79.292*** | −17.471*** | −22.654** |
| (10.272) | (12.282) | (19.191) | (4.980) | (4.218) | (15.744) | (6.211) | (11.151) | |
| Observations | 73 | 73 | 73 | 73 | 73 | 73 | 73 | 115 |
| R-squared | 0.858 | 0.829 | 0.861 | 0.882 | 0.746 | 0.868 | 0.671 | 0.96 |
| Standard errors in parentheses; *** p < 0.01, ** p < 0.05, * p < 0.1 |
Determinants of Export Performance in NMS
| (1) Value Added exports to EU: goods and services | (2) Value Added exports to the world: goods and services | (3) Gross exports to EU (GE) | (4) Value Added exports to EU: goods | (5) Value Added Exports to EU: services | (6) GE to EU: goods | (7) GE to EU: services | (8) Value Added exports to EU: advanced EU | |
|---|---|---|---|---|---|---|---|---|
| Upper secondary or tertiary educational attainment | 0.156* | 0.301*** | 0.417*** | 0.147*** | 0.023 | 0.415*** | 0.002 | 0.036 |
| Participation in continuous vocational training and skills upgrade | (0.083) | (0.099) | (0.156) | (0.040) | (0.034) | (0.128) | (0.050) | (0.042) |
| 0.147*** | 0.035 | 0.310*** | 0.107*** | 0.049*** | 0.259*** | 0.051*** | −0.005 | |
| (0.029) | (0.035) | (0.053) | (0.014) | (0.012) | (0.044) | (0.017) | (0.064) | |
| Inactivity trap | −0.0917*** | −0.032 | −0.195*** | −0.055*** | −0.029** | −0.155*** | −0.040** | 0.263*** |
| (0.026) | (0.032) | (0.051) | (0.013) | (0.011) | (0.042) | (0.017) | (0.052) | |
| Relative minimum wage | −0.083** | −0.047 | −0.369*** | −0.135*** | −0.004 | −0.369*** | 0.000 | −0.221*** |
| (0.038) | (0.045) | (0.061) | (0.016) | (0.013) | (0.050) | (0.020) | (0.033) | |
| Foreign investment and ownership environment | 0.905** | 0.998* | 2.961*** | 0.749*** | 0.492*** | 2.487*** | 0.474* | 1.804*** |
| (0.424) | (0.507) | (0.752) | (0.195) | (0.165) | (0.617) | (0.243) | (0.494) | |
| Share of exports processed by supply chain | 0.450*** | 0.571*** | 1.217*** | 0.136*** | 0.208*** | 0.904*** | 0.313*** | 0.259** |
| (0.118) | (0.141) | (0.186) | (0.048) | (0.041) | (0.152) | (0.060) | (0.085) | |
| Real effective exchange rate (ULC based) | −0.030 | −0.023 | −0.064 | |||||
| (0.019) | (0.022) | −0.087 | ||||||
| Weighted real GDP growth of trading partners | 0.055 | 0.162** | −0.082 | |||||
| (0.060) | (0.072) | −0.119 | ||||||
| Population | 0.475 | 1.327** | −0.622* | |||||
| (0.551) | (0.659) | −0.333 | ||||||
| PPP GDP per capita | 0.000 | 0.0003*** | ||||||
| (0.000) | (0.0001) | |||||||
| GDP weighted distance | 0.000 | −0.0009** | ||||||
| (0.000) | (0.0003) | |||||||
| Constant | −29.265*** | −45.783*** | −96.763*** | −10.829** | −13.305*** | −79.292*** | −17.471*** | −22.654** |
| (10.272) | (12.282) | (19.191) | (4.980) | (4.218) | (15.744) | (6.211) | (11.151) | |
| Observations | 73 | 73 | 73 | 73 | 73 | 73 | 73 | 115 |
| R-squared | 0.858 | 0.829 | 0.861 | 0.882 | 0.746 | 0.868 | 0.671 | 0.96 |
| Standard errors in parentheses; *** p < 0.01, ** p < 0.05, * p < 0.1 |
References
Andreica, M., Aparaschivei, L., Cristescu, A. and Cataniciu, N., 2010, Models of the Minimum Wage Impact upon Employment, Wages and Prices: the Romanian Case, Recent Advances in Mathematics and Computers in Business, Economics, Biology and Chemistry, Proceedings of the 11th WSEAS Int. Conf. MCBE 2010, pp. 104–109.
Baranowska-Rataj, A. and Magda, I., 2015, The Impact of the Minimum Wage on Job Separations and Working Hours among Young People in Poland, Institute of Statistics and Demography Working Paper No. 44/2015.
Fadejeva, L. and Krasnopjorovs, O., 2015, Labor Market Adjustment During 2008–13 in Latvia: Firm-Level Evidence, Latvijas Banka Working Paper No. 2/2015.
Hinnosaar, M. and Room, T., 2003, The Impact of Minimum Wage on the Labour Market in Estonia: An Empirical Analysis, Bank of Estonia Working Paper No. 8.
International Monetary Fund (IMF), 2014, The United States’ Staff Report for the 2014 Article IV Consultation, IMF Country Report No. 14/221, Washington, D.C.
International Monetary Fund, 2016, Getting Minimum Wages Right in Central, Eastern and Southeastern Europe, Forthcoming.
Kertesi, G. and Kollo, J., 2003, Fighting ‘Low Equilibria’ by Doubling the Minimum Wage? Hungary’s Experiment, IZA Discussion Paper No. 970.
National Bank of Romania, 2015, The Increase in the Minimum Gross Wage—Effects on the Labour Market, Inflation Report, May 2015.
Neumark, D., 2015, Reducing Poverty via Minimum Wages, Alternatives, FRBSF Economic Letter No. 2015–38, December 2015.
Neumark, D., Schweitzer, M. and Wascher, W. (2000), The Effects of Minimum Wages throughout the Wage Distribution, NBER Working Paper No. 7519.
Neumark, D., Schweitzer, M. and Wascher, W., 2005, The Effects of Minimum Wages on the Distribution of Family Incomes: A Non-Parametric Analysis, Journal of Human Resources, Vol. 40, No. 4 (Autumn 2005): 867–894.
Rahman, J., Stepanyan, A., Yang, J., and Zeng, L., 2015, Exports in a Tariff-Free Environment: What Structural Reforms Matter? Evidence from the European Union Single Market, IMF Working Paper No. 15/187.
Schnattinger, P., Jemec, N., Lozej, M., Vodopivec, M., Peternelj, P., 2015, Results of the 2014 Wage Dynamics Network Survey in Slovenia, Bank of Slovenia Working Paper No. 1/2015.
The United States’ Congressional Budget Office, 2014, The Effects of a Minimum Wage Increase on Employment and Family Income, Publication No. 4856, February 2014.
Voinea, L., and Mihaescu, F., 2012, A Contribution to the Public-Private Wage Inequality Debate, Economics of Transition, Vol. 20(2), p 315–337.
Prepared by Piyaporn Sodsriwiboon (EUR). The author thanks the discussants and participants at the seminar organized by the National Bank of Romania for their helpful comments, as well as staffs at IMF resident representative office in Romania for their excellent support on this research.
See for example Schnattinger and others (2015) for Slovenia and Fadejeva and Krasnopjorovs (2015) for Latvia.
Subject to data availability, it would also be interesting for future research to further analyze the public-private wage inequality in Romania. Voinea and Mihaescu (2012) find significant public-private wage premiums. Persistent increases in minimum wage or public wages regardless of productivity improvement could potentially be counterproductive and crowd out productive labor force in competitive sector.
To identify the wage pass-through at regional level, we estimate panel VARs to construct the average pass-through effects across 14 Central, Eastern and Southeastern Europe (CESE) countries including Estonia, Latvia, Lithuania, Czech Republic, Hungary, Poland, Slovak Republic, Slovenia, Bulgaria, Croatia, Romania, Serbia, Russia and Turkey.
i=1,2,..,N; t=1,2,..,T
yit = A0i(l)Yt–1+uit
Yt is the stacked version of yit, which is the vector of change in real average wages, employment growth, real labor productivity growth, change in term of trade and change in real minimum wages for each country i=1,2,…,N. The choice of variables follows Blanchard and Katz (1999) and Goretti (2008). All variables are in real terms using change in consumer price index as a deflator. Data are quarterly from 1995q1 to 2015q2. Panel is unbalanced. Lags included are chosen to minimize the information criterion statistics. The system is estimated using GMM method.
In line with the previous setting, the analysis draws on VAR framework for Romania at the overall wages as well as for wages by key economic sectors including industry, construction, service, and IT sectors. Yt=A0(t)+A1(l)Yt–1+utt=1,2,..,T and Yt is the vector of change in real average wages, employment growth, real labor productivity growth, and change in real minimum wages. Data are monthly from 2005m1 to 2015m7. Lags included are chosen to minimize the information criterion statistics. The system is estimated separately for each analysis.
Paid employed persons refer to those employed persons, including employees, self-employed and family workers, with gross employment income greater than zero. Gross employment income includes gross employee cash or nearcash income for employees, and gross cash benefits or losses from self-employment for self-employed and family workers. Paid employed persons refer to those employed persons with income greater than zero.
The pass-through effect on gross wage for Romania is estimated at around 0.45 percent to 1 percent increase in minimum wage.
