Economic data to be available from January beginning 2019

One of the biggest challenge for researchers is to collate data from different sources, especially if any time series analysis is intended. Our endeavour is to promote and facilitate research, for students, institution researchers, teachers, corporate and others, through providing collated time series data on India’s macro economic scenario from different data government data sources. All current data is provided for free to anyone who wants to download the data and work. The time series data that can save significant time on part of a researcher, is priced at a low price to cover the cost of that data collation. The following data will be available in our website from January beginning 2019.

Macro Economic Variables Years
Bank Rate ( Monthly) 2012 -2018
Cash Reserve Ratio ( Monthly) 2012 -2018
Cash-Deposit Ratio ( Monthly) 2012 -2018
Consumer Price Index ( Commodity Wise) 2011 -2018
Consumer Price Index (Annual) 2012 -2018
Consumer price index – Industrial worker wise 2012 -2018
Consumer Price Index – Industrial Worker- city wise 1998 -2012
Bank Credit ( Monthly) 2005 -2018
Credit-Deposit Ratio ( Monthly) 2012 -2018
Bank Deposits ( Monthly) 2005 -2018
Exports (Monthly) 2005 -2018
Foreign Exchange 2012 -2018
Foreign Trade (Monthly ) 1998 -2018
Gross Domestic Product annual ( Current and constant) 1961 -2018
Gross Domestic Product – Growth Rate 1961 -2017
Gross Domestic Product by sector and state    1990 – 2018
Gross Value Added and it’s components (Quarterly) 2011 -2018
Gross Value Added Sector wise ( Current and Constant)  2011 – 2018
Gross Value AddedState wise 1990 – 2015
Imports ( Monthly) 2005 -2018
Incremental Credit-Deposit Ratio ( Monthly) 2012 -2018
Incremental Investment-Deposit Ratio ( Monthly) 2012 -2018
Index of Industrial Production ( Sector Wise) 2005 -2018
Index of Industrial Production (Annual) 2005 -2018
Investment in Govt. Securities ( Monthly) 2005 -2018
Investment-Deposit Ratio ( Monthly) 2012 -2018
MCLR ( Monthly) 2012 -2018
Private final consumption annual ( current and constant) 1961 -2018
Private final consumption Expenditure ( product wise) 1999 – 2017
Whole sale price Index ( monthly- commodity wise) 1994 – 2018
Wholesale Price Index ( Annual) 2012 -2018

 

Understanding Spatial Economics can Help Business Decision Immensely

Dripto Mukhopadhyay

Evidences suggest that rapid economic growth is often associated with lopsided regional development. This has raised concerns from various quarters, including policy makers, that how to avoid intensifying of spatial inequalities with development efforts which are actually been aimed towards reducing the same. However, apart from being socially and politically de-stabilizing, this divergence in economic welfare has immense impact on business decision making. In simple terms, spatial inequality is the net result of the balance of forces of concentration and dispersion of economic activities.

In regional economics, two different models exist to address regional inequality. The first one is based on the standard neoclassical assumptions of constant returns to scale and perfect competition. Within this concept, the role of government involvement is relatively limited to infrastructure investments, which affects mobility of goods, labor and other factors. Governments may have little ability to influence the centripetal forces that are based on comparative advantage stemming from technology or resources. But Government may increase regional specialization or inequality by lowering the mobility of goods or may decrease extent of spatial inequality by lowering the mobility of factors.

On the other hand, the “new economic geography” models, commonly associated with Paul Krugman, contain five essential ingredients: increasing returns to scale that are internal to the firm, imperfect competition, trade costs,  endogenous firm location and most importantly, endogenous location of demand. The first four ingredients give rise to the agglomeration economies of home market effects, but the last ingredient, endogenous location of demand, creates the well-known process of circular causation which causes core-periphery regions to arise from initially symmetric regions.

The primary purpose of this article is to understand the likely implications of spatial inequality on business instead of understanding the genesis of spatial inequality. Several studies on India suggest that spatial inequality in India in increasing over time, as opposite to the Government’s efforts to reduce it. However, for you and me, this may be disturbing from social welfare point of view. But for business this understanding spatial inequality has immense bearing on business growth. Let me give you a simple example. As we know, Indian market is quite heterogeneous across geography as well as within geography. Assume a car manufacturer, producing small car, sedan, SUV and luxury cars wants to expand its presence in the country. The manufacturer is already an established player in small car market. Their current focus is to go beyond the small car market and to capture the sedan and SUV market. It is a big challenge for him to decide on how to expand his dealership as well as services in various parts of the country so that he can reach out and cater to the right segment of people for the sedan and SUV categories.

The car market is experiencing a transition from lower segment to higher segment since last few years. It is critical for the manufacturer to know where this trend of upgradation will be prominent in next 5 years or so. Only then he will be able to chalk out a plan to plan to cater demand at the right location. So, what all the manufacturer needs to know, as basic information? Following are a few critical ones as examples.

  1. How this upgradation trend has been recorded across geographies?
  2. What all are the factors that are driving this upgradation or transition of customers from lower segment to higher segment of cars?
  3. Has it been similar across the states of the country? Has it been similar within various cities or districts of the state?
  4. What will be scenario in next 5 years or 10 years from now regarding this upgradation?
  5. Based on the future scenario of upgradation across geographies, what will be the optimal way for creating new dealership development and service delivery plan?

 

All these can be answered through analyzing the dynamics of upgradation in passenger car with the help of spatial economics. Following is the flow of analysis that provides the answers to all critical questions that are important to this manufacturer.

  1. A through study of past trend of car sales for a significant period of time. This should be able to capture data as granular as possible. In majority of the cases, the data may be available at the state level and may be for selected cities.
  2. The analysis has to capture how this transition from one segment of car to others, reflecting upgradation, is happening by every state as well as from overall perspective.
  3. This needs to capture the demand drivers including economic parameters like changes in various components of domestic income (GDP), employment, household income, policy and access to finance, availability of various models across geographies and the similar ones
  4. An econometric model to be developed to measure elasticities and probabilities of upgradation and their nuances across states/cities.
  5. A demand forecast scenario by type of car to develop based on the econometric modelling and considering the likely changes going to happen on economic front across geographies in next 5 to 10 years.
  6. Mapping forecasted demand across states/cities to portray futuristic possibilities of upgradation and identify the clusters of higher demand of sedan and SUVs that are their focus segment to push in the market in next 5 to 10 years
  7. Prioritize geographies where the aggregate demand for the clusters located in closer proximity to each other from the point of view of supply chain point of view.

This can enable the manufacturer to take a firm decision based on a scientifically obtained results and insights to expand his dealership and services activities. This model is applicable to most of the sectors of economy including FMCG, Durables and similar ones. The rate of returns obtained through understanding spatial economics can be much higher compared to decisions taken through other means. Also, this reduces the probability for wrong investment decisions to a large extent.      

Sustainable Tourism

Sustainable tourism studies are part of our core research strengths. considering tourism industry contributing to more than 8% of total carbon emissions in the world, we consider this area of research can play key role in promoting sustainable business and sustainable development. Our tourism studies include forecasting, carbon emission estimation by tourism activities and likely solution towards that, tourists behaviour by segments, destination analysis and such areas of interests to business and policy makers.

Current studies in progress:

  1. Forecasting Foreign Tourist Arrivals to India from Top 20 Country of Origins till 2019 to 2024 – To be completed by March 2019 
  2. Forecasting Domestic Tourism in India by State 2019 to 2014 – To be completed by February end 2019
  3. Key Characteristics of Outbound Tourists from India – To be completed by January end 2019
  4. Tourism and Awareness about Environmental Degradation – A Case Study of Indian Domestic Tourists – To be completed by April 2019

Consumer Economics and Business Research

Consumer economics and business research solutions related studies are part of our core research areas. we study consumers with the help of primary survey and secondary data as well as our proprietary consumer demographic data at extreme granular level. Our studies on consumption behaviour analyses and the likely changes in future helps our extremely helpful to our clients for stress-free decision-making covering marketing, salesforce development, distribution network, supply chain building and related ones. Our solutions range from robust forecasting for various sectors to predict revenues for retailers at point locations to identifying locations for promoting premium products. We cover all sectors including FMCG, Automobile, Durables, Real estate, modern and traditional retail and other sectors of the economy. We cover entire geography of India, including all urban and rural space. Our capabilities of conducting large scale surveys across entire India and advanced analytics along with remote sensing and GIS skills help us addressing problems which many would dare to think of as solutions.

Current Studies in Progress:

  • A Study on Experimental Economics on Financial Product Market in India  – To be completed by April 2019 

This experimental study aims at understanding decision making behaviour of Indian consumer regarding financial product purchase. the study will cover 3000 plus households in Delhi for a certain income group to understand how do people make their decision for financial product purchase. The study is sponsored by Warwick university, NIPFP and IIM Ahmedabad.

  • Determinants and Their Relative Importance for Choosing Fast Food Joints – To be completed by Mid January 2019