User:Tughral Rasooli/sandbox

Role of IDBP in Industrial Development

Abstract: The IDBP (industrial Development Bank of Pakistan) plays a very vital role in the development and the growth of an economy. The study examines the relationship between the independent factor lending of IDBP and dependent factors like industrial growth rate, growth rate, unemployment rate and purchasing power and how these factors effect on industrial development. According to the research the dominating factor among all the factors is growth rate. After applying statistical tools or techniques we find out that lending rate is so much effective in the economical conditions of countries. . If lending rate is increasing than it will have really negative effect on industrial sector and economic growth whereas due to the increasing in all the lending of IDBP rate unemployment in the country is also increased for every economy growth. Lending of IDBP is so much effective and it really contributes so much in the effective growth of the economy Introduction: The concept of development and the process of industrialisation are synonymous. The dominant criteria for development have been closely linked with economic well-being and quality of life. They are a major contributory factor in generating employment opportunities, improving technical skills and raising income levels. In developing countries such as Pakistan, various policy measures were adopted to accelerate the industrialisation process. In the absence of developed capital and financial market, the financing of industrial enterprises in Pakistan is characterised by the development finance institutions established by the government. The Industrial development bank of Pakistan is one of the oldest Financing institution which provide financing and help them to run the cycle of manufacturing sector of Pakistan, Over the years, The banks of Pakistan plays an important role in the development and growth of the SMEs sector. IDBP is the sector that introduced the idea to invest money in development sector like industrial, economic sector.

The ideas contribute a lot and were appreciated in financial and economic sector. This is how Industrial development bank got famous and take part in growing up the economy, and also introduce in different countries. The main objective of this bank is to develop the economy and industrial sector weather it is working on small or large scale. All these years, the Industrial Development Bank worked immensely in order to achieve the goals and targets that had been set-up and they achieved full success in it Today there are many branches of industrial bank almost all over the world, and also contribute a lot in developing the industrial sector, and if we are talking about the under develop countries like Pakistan, then this type of industrial development bank helps a lot in developing the economy of a country Features: The Industrial Development Bank of Pakistan is one of the most leading and oldest bank of Pakistan. It was made in 1961. Prior to nationalization of banks in January 1974 the IDBP had a paid up capital of Rs. One billion. The IDBP plays a vital role in bosting up the economy of Pakistan, and industrial sector. IDBP has also become an important component of the financial sector of Pakistan .The Industrial development bank also provide short and long term loans in bullish up the economy and also change the old projects. It also provides financial and management ideas to its clients in order to run the industrial cycle. In IDBPs Govt have 57% of shares, State bank of Pakistan have 36% shares and provincial government have 7% shares and other public sector. Another feature of IDBP is that, It also dealing with foreign bank, The IDBP extends all kinds of merchant, investment and commercial banking services to its clients which include provision of short term loans, trade financing, lease financing, guarantees. The IDBP provides a full concentration in rising up the industrial sector. The IDBP also performed as a Commercial banking, The IDBP thus act as a commercial bank in addition to its role as a growth of financial institution. Another feature of IDBP is the Universal banking. In 1989, the IDBP began to provide universal banking facilities to its clients. It is providing combination of commercial banking and investment banking services to its clients.. The financial health of the IDBP is not satisfactory at present. It is facing serious problems of non-payment of loans. This has adversely affected the profitability and liquidity of the Bank. The major factors contributing to its low performance are (i) inadequate legal and judicial system (ii) deteriorating culture system (iii) general slowdown of the economy (iv) adverse impact of sanctions, etc.

Literature review:

Emilia Bonaccorsi di Patti(2005) conducted a research on Financial sector liberalization, bank privatization, and eﬃciency, Evidence from Pakistan, in his research he concluded that The Pakistani banking system has been transformed over the past 15 years through liberalization, the entry of private banks, the privatization of public-sector banks, and the tightening of prudential regulations. The eﬀects of these changes on bank productivity and relative eﬃciency are investigated using various techniques. He also concluded that the privatization of bank also improves the industrial sector of Pakistan especially the SME banks trend helps the poor people in opening their small industry the SMEs banks also provide the medium and long term loans to people.Idbp plays a very important role in developing and the growth of economy, these banks also provides medium and long term loans for the industrial sector. It also provides the ideas and future for casting for the banks and let them update according to the economic condition. Financial market deregulation and liberalization has transformed the banking systems of a large number of countries over the last two decades, and especially in some developing countries, Pakistan is one of those countries.

Nicola Cetorelli (1999) conducted a research on Banking Market Structure, Financial Dependence and Growth, International Evidence from Industry Data, in his research paper he explores the effects of banking market structure on growth. The research shows that there is a positive relationship between the level of development of the banking sector of an economy and its long-run out-put growth in industrial sector, however about the role played by the market structure of the banking sector on the dynamics of capital accumulation. This paper provides evidence that bank concentration promotes the growth of those industrial sectors that are more in need of external finance by facilitating credit access to younger firms. He also derives out that the amount of credit or money that the bank use for productive work is one of the most significant work and a good indicator of the industrial and economics growth. The development of financial institution and the development of financial growth will also effects the growth of industrial sector and in resulting in the growth of economy as well.

Manas Mukhopadhyay, (2009), conducted a research on Role of Development Banks in Promoting Industrial Energy Efficiency, India Case Studies in his research he derives out that the Industrial Development Bank of India (IDBI) is the main institution in developing the Indian industrial banks. There annual budget is about 6billion$. By recognizing the importance of energy and industrial development in India the Asian Development bank provides them $150million to IDBI for full filling their needs. These funds were used in cement, steel, paper, sugar and other industries. ADB also provide finance to Indian industrial sector in order to strengthen IDBI capabilities and try to solve there conflicts and problems .The ADB also focuse on the IDBI capibilities, energy-intensive sectors, and training and data needs to improve its lending. The findings of the TA reveal a need to (1)	To keep eye on the project. (2)	Increase awareness of ee/em components.

In the end he said that the technical assistance awareness providing help in improving energy Efficiency in ten industrial sectors of the Indian economy. It examined the barriers to improving energy efficiency and suggested ways by which IDBI could increase and improve its lending for energy efficiency projects. The study represent technical options that were common to all sectors, such as efficient lighting, high efficiency electric motors, pumps, compressors and drives, computerized process controls, waste heat utilization, and installation of captive power plants. In addition, it identified options that were process-oriented and thus specific to each type of industry.

NICOLA CETORELLI (2003), conducted a research on real effect of bank competition in his research he explores that there are few question arises that, does banking market power contribute to the formation of non ﬁnancial industries populated by few, large ﬁrms, or does it instead enhance industry entry? The paper derives out a new dimension of analyzing and check the efficiency of the banks that how they concentrate on the market structure and financial institution. Exploiting such signiﬁcant innovations affecting the banking industries of EU countries, this paper explores whether changes in bank competition have in fact played a role on the market structure of nonﬁnancial industries. Empirical evidences derived from a panel of manufacturing industries in 29 OECD countries, the evidence suggests that the overall process of enhanced competition in EU banking markets has led to markets in nonﬁnancial sectors characterized by lower average ﬁrm size. He also derives out that contributed to investigate a new dimension of analysis of the economic role of bank concentration and competition. The results show that sectors where old ﬁrm are more in need of external ﬁnance are of larger size if they are in countries whose banking sector is more concentrated.

Data and methodology We conducted research in banking sector of Pakistan in order to find out well lending is contributing in the growth of our economy. Pour model consist on the variables for which data can be conducted from any secondary sources to collect data. We collected data from very authentic source WDI, SBP ad KSE,and Economic profile of Pakistan. We collected data of last 11 years from 2000 to 2011 of our variables. After collecting data we use statistical tools and software SPSS and applies descriptive, correlation, and regression techniques simple regression on it and the hypothesis we made are following.

Hypothesis: Developing and testing the hypothesis to check whether it has an effect or not

Ho:	There is no relation between industrial growth rate and lending rate. H1:	There is relation between industrial growth rate and lending rate.

Ho:	There is no relation between growth rate and lending rate. H2:	There is relation between growth rate and lending rate.

Ho:	There is no relation between unemployment rate and lending rate. H3:	There is relation between unemployment rate and lending rate.

Ho:	There is no relation between purchasing power and lending rate. H4:	There is relation between purchasing power and lending rate.

Research Question Main Question... Do our variables (industrial growth rate, growth rate, unemployment rate etc) are affected by lending Sub Question… 1.	Do you think lending affect industrial growth rate? 2.	Does lending can affect growth rate? 3.	Do you think that lending can affect unemployment? 4.	Do you think that lending can affect purchasing power? Empirical Analysis:-

Descriptive analysis:

In descriptive analysis we take five variables one is independent variable that is lending and other four are dependent variables.

Descriptive Statistics N      Minimum	Maximum	   Mean	        Std. Deviation growth rate	                  11	    1.72	8.96	   4.5845	    2.39846 purchasing power	          11	    1819.00	2787.00	   2.3428E3         367.22277 industrial growth rate	          11	   -1.90	13.10	   5.7273	    4.35685 unemployment rate	          11	    6.19	8.27	   7.0618	    .89930 lending	                          11	    6.00	15.00	   10.2727	     3.58025 Valid N (listwise)                11

In above table we have taken data of last 10 years, and independent variable is lending and dependent variable is growth rate. Growth rate maximum value is 8.96 and its minimum value is 1.72, its mean value is 4.5845 and its standard deviation is 2.39846. Another dependent variable is Purchasing power, its maximum value is 2787.00 and its minimum value is 1819.00, its mean value is 2.3428E3, and its standard deviation is 367.22277. In Industrial growth rate, its maximum value is 13.10 and its minimum value is -1.90, its mean value is 5.7273. and its standard deviation is 4.35685. In Unemployement rate its maximum value is 8.27 and its minimum value is 6.19, its mean value is 7.0618 and its standard deviation is .89930. In Lending the independent variable, its maximum value is 15.00 and its minimum value is 6.00, its mean value is 10.2727 and its standard deviation is 3.58025. .

Correlation Analysis:- Correlations

growth rate	  industrial 	  unemployment rate     purchasing power	lending growth rate

growth rate:

Pearson Correlation	1	       .798**	             .274	         -.126	          -.241 Sig. (2-tailed)		               .003	              .415	          .713	           .475 N	               11	         11	               11	           11	            11

industrial growth rate

Pearson Correlation	.798**	         1	               .413	           -.302	    -.434 Sig. (2-tailed)	                        .003		       .207	            .367	    .182 N	                11	          11	                11	            11	             11

unemployment rate

Pearson Correlation	.274	          .413	                 1	             -.956**	      -.965** Sig. (2-tailed)	                          .415	                .207		      .000	      .000 N	                11	            11	                 11	                11	       11 purchasing power

Pearson Correlation	 -.126	           -.302	         -.956**	         1	       .977** Sig. (2-tailed)	                           .713	          .367	               .000	       .000 N	                11	             11	                   11	                 11	        11 lending

Pearson Correlation	-.241	           -.434	           -.965**	         .977** 	 1 Sig. (2-tailed)	                            .475	            .182	         .000	        .000 N	                 11	              11	             11	                  11	         11
 * . Correlation is significant at the 0.01 level (2-tailed).

Correlation: The correlation coefficient measure the strength of linear relationship between two or more numerical variables, so we use Pearson correlation. When we have take two variables that are scale and normal. In correlation table, we take significance value it at 0.01 and 0.05 level it is (2 tailed) test

Relationship between growth rate and industrial growth rate In this table we investigate if there was a statistically significance association between growth rate and industrial growth rate a correlation was computed. Both the variables were approximately normal and there is linear relationship between them hence fulfilling the assumptions for Pearson’s. (R) Is calculated R 0.798, P > 0.003 relating that highly significance relationship between the variable, the positive sign shows the there is positive relationship between growth rate and industrial growth rate. Variables: - Growth rate, industrial growth rate R=0.798 P > 0.003 Relationship between growth rate and unemployement rate To check if there was a statistically significance association between growth rate and unemployment rate, a correlation was computed. Both the variables were approximately normal and there is linear relationship between them hence fulfilling the assumptions for Pearson’s correlation. (R) Is calculated that is R 0.274, P< 0.445 the calculated R values greater than significance level and the value shows that there is positive relationship between and is shows there is relationship between these variables. Variables: - growth rate, unemployement rate R = 0.798, P < 0.445 Relationship between growth rate and purchasing power To check if there was a statistically significance association between growth rate and purchasing power, a correlation was computed. Both the variables were approximately normal and there is linear relationship between them hence fulfilling the assumptions for Pearson’s correlation. (R) Is calculated that is R = -0.126, P < 0.713 the calculated R values lower than significance level and the value shows that there is negative relationship between and is shows there is no relationship between these variables. Variables: - growth rate, purchasing power R = -0.126, P <0.713 Relationship between growth rate and lending To check if there was a statistically significance association between growth rate and lending, a correlation was computed. Both the variables were approximately normal and there is linear relationship between them hence fulfilling the assumptions for Pearson’s correlation. (R) Is calculated that is R = -.241, P > 0.475 the calculated R values greater than significance level and the value shows that there is negative relationship between ad is shows there is no relationship between these variables. Variables: - growth rate,lending R = -0.241, P > 0.475 Relationship between Industrial growth rate and Unemployment We investigate if there was a statistically significance association between industrial growth rate and unemployment correlation was computed. Both the variables were approximately normal and there is linear relationship between them hence fulfilling the assumptions for Pearson’s. (R) Is calculated R=.413, P < .207 relating that highly significance relationship between the variables, the positive sign shows the there is positive relationship between industrial growth rate and unemployment. Variables: - industrial growth rate,unemployment R = 0.413, P <0.207 Relationship between industrial growth rate and purchasing power We investigate if there was a statistically significance association between industrial growth rate and purchasing power  and services a correlation was computed. Both the variables were approximately normal and there is linear relationship between them hence fulfilling the assumptions for Pearson’s. (R) Is calculated R -0.302, P = 0.367 relating that highly significance relationship between the variables, the negative sign shows the there is negative relationship between industrial growth rate and purchasing power. Variables: - industrial growth rate, purchasing power R = -0.302,p>.367

Relationship between industrial growth rate and lending

We investigate if there was a statistically significance association between industrial growth rate and lending a correlation was computed. Both the variables were approximately normal and there is linear relationship between them hence fulfilling the assumptions for Pearson’s. (R) Is calculated R -0.434, P > 0.182 relating that highly significance relationship between the variables, the positive sign shows the there is positive relationship between consumer goods and exchange rate. Variables: - industrial growth rate, lending R = -0.434, P > 0.182 Relationship between unemployement rate and purchasing power We investigate if there was a statistically significance association between unemployement rate and purchasing power a correlation was computed. Both the variables were approximately normal and there is linear relationship between them hence fulfilling the assumptions for Pearson’s. (R) Is calculated R -0.956, P > 0.000relating that highly significance relationship between the variables, the negative sign shows the there is negative relationship between unemployement rate and purchasing power. Variables: - unemployement rate, purchasing power R = 0.466, P > 0.000 Relationship between unemployement rate and lending

To check if there was a statistically significance association between unemployment rate and lending a correlation was computed. Both the variables were approximately normal and there is linear relationship between them hence fulfilling the assumptions for Pearson’s correlation. (R) Is calculated that is R = 0.04, P > 0.000 the calculated R values less than significance level and the value shows that there is negative relationship between ad is shows there is no relationship between these variables. Variables: - unemployment rate, lending R = -0.965, P >0.000

Relationship between Purchasing power and lending We investigate if there was a statistically significance association between purchasing power and lending a correlation was computed. Both the variables were approximately normal and there is linear relationship between them hence fulfilling the assumptions for Pearson’s. (R) Is calculated R = 0.977, P > 0.000 relating that highly significance relationship between the variables, the positive sign shows the there is positive relationship between purchasing power and lending. Variables: - purchasing power, lending R = 0.266, P > 0.199

Regression analysis:-

Simple Regression

Model	                    (Constant)	    Adj. R²	  F	      Sig	  B	   t – value	  Sig

Industrial growth rate	                11.151	     .098  	 2.087	     0.182	-.528	  -1.445          0.182

Growth rate	                6.245	    -.046	 .556	     .475  	-.162	   -.746	  0.475

Unemployment rate	        9.553       .925        123.626      0.000	-.243	   -11.119	  0.000

Purchasing power	        1313.513    .949	 187.930      0.000	 100.198     13.709	  0.000 Independent variable: lending

Relationship between Industrial Growth and lending: In simple regression the results were statistically significant the industrial growth and lending F = 2.087, p<0.182. The identified equation to understand this relationship was Industrial growth rate and lending. The adjusted R square value was 0.098. And estimated regression equation:-

Y=a+bx Y= 11.151-0.528x Here coefficient for lending is -0.528 so it explains every unit increase in lending rate will decrease industrial growth rate 52%if all other variables are constant.satndard error associated with it is 0.365.

Relationship between Growth rate and lending: In simple regression the results were statistically significant the growth rate and lending F = .556, p>0.000 The identified equation to understand this relationship was growth rate and lending. The adjusted R square value was -0.046. And estimated regression equation:- Y=a+bx Y= 6.245-0.162x Here coefficient for lending is -.162 so it explains every unit increase in lending rate will decrease growth rate 16%if all other variables are constant.satndard error associated with it is 0.217.

Relationship between Unemployment rate and lending:

In simple regression the results were statistically significant the Unemployement rate and lending F = 123.626, p<0.172. The identified equation to understand this relationship was unemployment rate and lending. The adjusted R square value was 0.925. And estimated regression equation:- Y=a+bx Y= 9.553-0.243x

Here coefficient for lending is -.243 so it explains every unit increase in lending rate will decrease unemployment rate 24.3%.if all other variables are constant.satndard error associated with it is 0.22.

Relationship between purchasing power and lending: In simple regression the results were statistically significant the Purchasing power and lending F = 187.930, p>0.000. The identified equation to understand this relationship was purchasing power and lending. The adjusted R square value was 0.949. And estimated regression equation:- Y=a+bx Y= 1313.513+100.198x

Here it shows positive relation of lending and purchasing power if one unit of lending is increased then purchasing power will increase by 100.

Conclusion:After applying statistical tools or techniques we find out that lending of IDBP rate is so much effective in the economic conditions of countries. Like Pakistan. It is contributing so much in the effective growth of industrial sector as well as the growth of economy. If lending rate of IDBP is increasing than it will have really negative effect on industrial sector and economic growth whereas due to the increasing in all the lending rate of IDBP unemployment in the country is also increased for every economy growth. Lending of IDBP is so much effective and it really contributes so much in the effective growth of the economy. We find out that if is lending rate is increased then industrial growth and growth rate of the economy will be decrease and unemployment in the economy will increased but purchasing power has some positive relation with lending of IDBP in our findings so lending rate of the banking sector plays the vital role in the economical stability to increase industrial growth and growth of the economy for full employment in the economy, lending rate of the banking sector of the economy will be at minimum level then it will provide different growth opportunities.

Reference: Nicola cetorelli (2009), Banking Market Structure, Financial Dependence and Growth, International Evidence from Industry Data

Manas Mukhopadhyay, Dalal Consultants and Engineers (1999), Role of Development Banks in Promoting Industrial Energy Efficiency, India Case Studies.

Nicola cetorelli,real effect of bank competation, Vol. 36, No. 3 (June 2004, Part 2) Published in 2004 by The Ohio State University Press.

Emilia Bonaccorsi di Patti (2005), Financial sector liberalization, bank privatization, and eﬃciency: Evidence from Pakistan, Journal of Banking & Finance 29 (2005) pp (2381–2406). www.googlescholar.com