Preparing a model to showcase industry expertise using the data point system

To showcase industry expertise I developed a model for any particular industry and based on the model the graph was to be prepared. The main motive of developing such model was to show our expertise in the industry and keep up to date with latest trends and changes. To achieve the main objective of such model there are some points which should I considered:

  • Industry should be related to our research studies
  • Data for the variable should be available on monthly basis
  • Model should be dynamic so that more variables can be included in future, if required
  • Model should be based on point system so that the trend can be shown in single graph

Preparing the model for the manufacturing sector in India

Given the above points I developed a model showing the efficiency of the manufacturing sector in India. Before deciding the industry and technique, it was important to conduct a thorough research about the availability of the monthly data for the Indian macroeconomic variables. The study in-focus is related to foreign direct investment and its impact on the Indian economy. After reviewing different government websites and open data sources I finalized four variables for which the data was available freely on monthly basis. The four variables are:

  • Index of industrial production
  • Total exports
  • Foreign direct investment
  • Bank credit

Once the variables are finalized then the task was to connect the four variables and create a data point system for the the manufacturing sector. However it was important to use some technique to integrate all the variables and come out with a single point system.

Among the four variables bank credit and foreign direct investment were used as input by the manufacturing sector. On the other hand exports and the index of industrial production is the indicator for the output of this sector. So there are two input variables and two output variables for the manufacturing sector. On the basis of the categorization of the variable I decided to measure the efficiency of the manufacturing sector in India. The efficiency can be measured for any combination of input and output and the efficiency value always lies between 0 and 1. Here 1 represents the efficient, in other words if some entity has efficiency value of 1, it is using the input optimally to produce maximum output.

Technique and the software used for the model

Model measuring the efficiency of manufacturing sector in India using two input and two output

Model measuring the efficiency of manufacturing sector in India using two input and two output

There are different software and techniques which can be used to measure the efficiency of an entity. However, among all the available softwares, Data Envelopment Analysis Program (DEAP) comes out to be the best option for my model. This is because DEAP allows the user to choose different model based on their research objectives.

For example: one can use either input oriented or output oriented model based on whether are focusing on minimization of input or maximisation of the output. Similarly, one can choose between different returns to scale, namely the increasing returns to scale (IRS), constant returns to scale (CRS) and decreasing returns to scale (DRS). The number of input and output is dynamic. Furthermore the software is freely available and easy to use.

Results and graph presentation

I have collected the monthly data for all the four variables for the time period January 2016- December 2016 to measure the efficiency of the manufacturing sector. For this model I have selected the output oriented model because the manufacturing sector do not have much control in the input used for this mode. The equation for the output oriented model can be written as;

maxf,l f,

st         –fqi + Ql ³ 0,

xiXl ³ 0,

N1¢l = 1

l ³ 0

Where,

K is the number of inputs, M is the number of outputs and I is the number of firms

xi is the Kx1 vector of inputs of i-th firm

qi is the Mx1 vector of outputs of ith firm

X is Kx1 input matrix. Q is the Mx1 output matrix

f is the scaler : 1£ f £ ¥

Technical efficiency is 1/f

Using the above model for the manufacturing sector in DEAP gives the following result.

Efficiency of the manufacturing sector in India from Jan-Dec

Efficiency of the manufacturing sector in India from Jan-Dec

As discussed above the sector is performing efficiently in the month of March, May, June and December. In all other months the value of efficiency is less than one. This means that the sector was not able to utilize its input to produce maximum possible output.

Indra Giri

Indra Giri

Senior Analyst at Project Guru
He completed his Masters in Development Economics from South Asian University, New Delhi. His areas of interest includes various socio development issues like poverty, inequality and unemployment in South Asia. Apart from writing for Project Guru he loves to travel and play football in his spare time.
Indra Giri

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