India's unemployment to reach 6.75% in April, highest since July 2017; weekly rate on April 8 was even higher, 7.41%
By Our Representative
India's top data consultancy firm, Centre for Monitoring Indian Economy (CMIE), has estimated that the weekly unemployment rate spiked to 7.41 per cent in the week ended April 8, which is the highest weekly unemployment rate in 78 weeks, or since early October 2016. Pointing out that the monthly estimate are based on different set of crieteria, CMIE says, it would be 6.75 per cent in April 2018, the highest since July 2017.
In an analysis based on the top consultancy firm's data, Mahesh Vyas, its senior expert, has said, while it is true that a solitary spike does not always tell a true story, and it could possibly be an "outlier", the fact remains, the unemployment rate in India was around 7.25 per cent during the first fortnight of April 2018, which suggests that "this unemployment rate is high compared to the levels observed in a fairly long time."
Pointing out that this unemployment rate is "significantly higher than the observed average of around 6.5 per cent in the preceding weeks", the CMIE expert says, this suggests, "the preceding week’s 7.41 per cent does not look like an outlier but, possibly, looks like an indication that the unemployment rate has inched up again."
Noting that the unemployment rate has been "rising since July 2017 when it clocked a mere 3.4 per cent", Vyas says, "The rate rose quickly to 5 per cent by October 2017 and then stabilised around 5 per cent for three months before spurting to 6 per cent in February and March 2018."
The senior expert predicts, "Now, with data for two weeks in hand, it seems poised to rise higher in April. It would be safe to assume that the rate has risen and April is likely to report an unemployment rate that would be the highest since demonetisation."
Pointing towards the type of data on which he has based his analysis, Vyas, who is managing-director and CEO of CMIE, says, "Weekly estimates are a close approximation of the monthly estimates. Weekly estimates are based on a sample of about seven thousand households that provide the employment/unemployment status of nearly 25,000 individuals that inhabit these sample households."
At the same time, he states, "However, there are a few details that one needs to keep in mind while extrapolating weekly estimates of unemployment to monthly estimates. First, weekly estimates are for the week ended Sunday and months don’t necessarily end on Sundays".
Pointing out that this is a "very minor problem", Vyas says, "Secondly, weekly estimates are not adjusted for non-responses and monthly estimates are adjusted for non-responses. This makes the monthly estimates a little more reliable than the weekly estimates. You are justified if you ask, so, why don’t we just adjust the weekly estimates for non-responses."
The answer, according to him, is that "the weekly sample is a little fluid because of operational problems. Survey execution at a household that is supposed to be surveyed in a particular week may have to be shifted to the next week because of a local problem."
"For example", he says, "In the last couple of weeks, internet services were temporarily suspended in many parts of the country to contain the several protests that have erupted. This hampered survey execution temporarily."
Comments the top expert, "As an aside, it is not a good sign when a country has to suspend internet services repeatedly from entire regions. It brings far too many activities to a halt -- including tax filings, regulatory filings, financial transactions and settlement of bills."
Thirdly, and more substantively, Vyas says, weekly estimates are based on "a survey design that uses appropriate weights for rural and urban India at the all-India level. The monthly estimates are based on a survey design that uses appropriate weights for rural and urban India at the state-level. Thus, there is a much greater stratification deployed in the monthly estimates than in the weekly estimates. This again, makes the monthly estimates more reliable than the weekly estimates."
According to Vyas, "The total number of strata used in the monthly estimates is 49. If the responses from any of these is less than a minimum requirement then the data from such strata is not used because they can skew the results. This greater stratification and stringent requirements on the sample make the monthly estimates fairly robust."
Given this framework, says Vyas, Data of the recent past suggest that weekly estimates overestimate the unemployment rate, on an average, by about 50 basis points compared to the monthly estimates. This implies that the 7.25 per cent unemployment rate we see in the first fortnight of April 2018 could well be 6.75 per cent."
Underlining that "even this is significantly higher than than the unemployment rate of 6.2 per cent in March and 6.1 per cent in February", Vyas says, be that as it may, "It is apparent that the unemployment rate which has been rising steadily over the past eight months will continue to rise during the ninth month -- April 2018."
India's top data consultancy firm, Centre for Monitoring Indian Economy (CMIE), has estimated that the weekly unemployment rate spiked to 7.41 per cent in the week ended April 8, which is the highest weekly unemployment rate in 78 weeks, or since early October 2016. Pointing out that the monthly estimate are based on different set of crieteria, CMIE says, it would be 6.75 per cent in April 2018, the highest since July 2017.
In an analysis based on the top consultancy firm's data, Mahesh Vyas, its senior expert, has said, while it is true that a solitary spike does not always tell a true story, and it could possibly be an "outlier", the fact remains, the unemployment rate in India was around 7.25 per cent during the first fortnight of April 2018, which suggests that "this unemployment rate is high compared to the levels observed in a fairly long time."
Pointing out that this unemployment rate is "significantly higher than the observed average of around 6.5 per cent in the preceding weeks", the CMIE expert says, this suggests, "the preceding week’s 7.41 per cent does not look like an outlier but, possibly, looks like an indication that the unemployment rate has inched up again."
Noting that the unemployment rate has been "rising since July 2017 when it clocked a mere 3.4 per cent", Vyas says, "The rate rose quickly to 5 per cent by October 2017 and then stabilised around 5 per cent for three months before spurting to 6 per cent in February and March 2018."
The senior expert predicts, "Now, with data for two weeks in hand, it seems poised to rise higher in April. It would be safe to assume that the rate has risen and April is likely to report an unemployment rate that would be the highest since demonetisation."
Pointing towards the type of data on which he has based his analysis, Vyas, who is managing-director and CEO of CMIE, says, "Weekly estimates are a close approximation of the monthly estimates. Weekly estimates are based on a sample of about seven thousand households that provide the employment/unemployment status of nearly 25,000 individuals that inhabit these sample households."
At the same time, he states, "However, there are a few details that one needs to keep in mind while extrapolating weekly estimates of unemployment to monthly estimates. First, weekly estimates are for the week ended Sunday and months don’t necessarily end on Sundays".
Pointing out that this is a "very minor problem", Vyas says, "Secondly, weekly estimates are not adjusted for non-responses and monthly estimates are adjusted for non-responses. This makes the monthly estimates a little more reliable than the weekly estimates. You are justified if you ask, so, why don’t we just adjust the weekly estimates for non-responses."
The answer, according to him, is that "the weekly sample is a little fluid because of operational problems. Survey execution at a household that is supposed to be surveyed in a particular week may have to be shifted to the next week because of a local problem."
"For example", he says, "In the last couple of weeks, internet services were temporarily suspended in many parts of the country to contain the several protests that have erupted. This hampered survey execution temporarily."
Comments the top expert, "As an aside, it is not a good sign when a country has to suspend internet services repeatedly from entire regions. It brings far too many activities to a halt -- including tax filings, regulatory filings, financial transactions and settlement of bills."
Thirdly, and more substantively, Vyas says, weekly estimates are based on "a survey design that uses appropriate weights for rural and urban India at the all-India level. The monthly estimates are based on a survey design that uses appropriate weights for rural and urban India at the state-level. Thus, there is a much greater stratification deployed in the monthly estimates than in the weekly estimates. This again, makes the monthly estimates more reliable than the weekly estimates."
According to Vyas, "The total number of strata used in the monthly estimates is 49. If the responses from any of these is less than a minimum requirement then the data from such strata is not used because they can skew the results. This greater stratification and stringent requirements on the sample make the monthly estimates fairly robust."
Given this framework, says Vyas, Data of the recent past suggest that weekly estimates overestimate the unemployment rate, on an average, by about 50 basis points compared to the monthly estimates. This implies that the 7.25 per cent unemployment rate we see in the first fortnight of April 2018 could well be 6.75 per cent."
Underlining that "even this is significantly higher than than the unemployment rate of 6.2 per cent in March and 6.1 per cent in February", Vyas says, be that as it may, "It is apparent that the unemployment rate which has been rising steadily over the past eight months will continue to rise during the ninth month -- April 2018."
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