Monthly car, truck, tractor and two-wheelers and three-wheelers sales data are available at dealer levels in detail. Again, this ties to consumption and commercial demand, and the health of specific segments of the economy. For example, tractor sales and two-wheeler sales tie up with rural consumption. Truck sales generally indicate strong activity. In addition, industries such as cement and steel log monthly despatches, indicating construction activity. Export and import data is also issued, along with power and fuel consumption data. So are telecom subscriber numbers and average revenues per user. All these have obvious links to economic activity. On the financial side, corporate credit rating data is released regularly, along with news of restructured loans. Housing mortgage data is available, quarter by quarter. The amount of external borrowing, of bank credit, of foreign direct investment intake, of disaggregated foreign institutional investor buys and sells, etc, is also available.
As of now, very little, if any, of this 'high-speed' data supports the official GDP projection of strong and accelerating growth. But, the data in itself are interesting. It outlines some degree of rural slowdown. Tractor and two-wheeler sales are down. The profits of fast moving consumer goods companies profits are down. Payments under the rural job guarantee scheme have swelled. Rural inflation seems higher. The data also indicate the urban dweller is not all that well off, though these areas are doing comparatively better than the rural ones. Housing mortgages have grown slowly, while commercial bank credit growth has been low. However, credit card usage seems to have risen.
Some indicators are difficult to track. Advertising, for example, is a useful leading indicator but the information is rather anecdotal. This is a fragmented sector, with multiple unlisted entities of various sizes. Ad revenues are said to be up, a good sign if it's private sector advertising, which generally correlates to growth. However, disaggregating of government advertising (which often bears no relationship to economic activity) inside meaningful time frames is hard, due to data lags. The biggest black hole in official data is on employment. There are several agencies - the National Sample Survey Organisation (NSSO), Census of India and the Labour Bureau, for instance - tracking this but the data are lagged. The comprehensive sets from NSSO and the Economic Census are lagged by five years and, therefore, useless, except to a historian. More recent jobs data are nowhere near comprehensive. Taken together, the employment data is often contradictory and also difficult to match, due to different methods and time frames. India has nothing resembling the US non-farm payroll data that is released month-on-month. Similar numbers could probably be created at least on a quarterly basis, using permanent account number, tax deductions and Aadhaar among others. Quite recently, the quarterly Manpower Employment Outlook Survey started to provide a leading indicator for job watchers, by interviewing employers across sectors to gauge their attitudes to hiring in the near future. It remains to be seen how accurate this is. The latest two surveys (covering October 2015 till March 2016) suggest there will be net hiring across sectors. These classify the companies surveyed into seven sectors and employers across all these had said they'd be hiring in January-March. Optimism seems high in transportation, retail (including e-commerce) and utilities.
While it is not possible to trade directly on the basis of this data, it is possible to get leads to many potential areas of interest by looking at high-speed indicators. While the controversy about GDP has led to short-term confusion, and even to conspiracy theories, it should have positive outcomes in the long run. Data quality could improve as more people search for multiple sources of reliable data.
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