Research Article

Development of Livestock and Productivity of Labour in Pakistan: An Empirical Work

Muhammad Shahid1*, Mehmood Shah2, Adiqa Kiani3 and Farhat Parveen4

1Head of Department of Economics at Govt. Post Graduate College Bhakkar Punjab, Pakistan; 2Chairman Department of Economics Gomal University Dera Ismail Khan, Pakistan; 3Associate professor Department of Economics, Federal Urdu University of Arts Science and Technology, Islamabad, Pakistan; 4Government College for Woman Darya Khan, Pakistan.

Received | August 27, 2018; Accepted | February 05, 2019; Published | May 21, 2019

*Correspondence | Shahid Amir, Head of Department of Economics at Govt. Post Graduate College Bhakkar Punjab, Pakistan; Email: [email protected]

Citation | Shahid, M., M. Shah, A. Kiani and F. Parveen. 2019. Development of livestock and productivity of labor in Pakistan: an empirical work. Sarhad Journal of Agriculture, 35(2): 647-653.

DOI | http://dx.doi.org/10.17582/journal.sja/2019/35.2.647.653

Keywords | Livestock, Human development index, Government fixed capital, Inflation rate, Governance

Introduction

The livestock has emerged as income raising and generating sector for more than 70 % population of the rural area in a multidimensional way. It shares 11% to Gross Domestic production and 58.9 % contributes the agriculture sector and 11.1 percent to GDP IN 2017-18. In the last two decades it has progressed 5.6 % more than the growth rate of over all agriculture sector. Livestock in the agriculture sector has the potential to tackle seasonal fluctuations, deficiency of inputs and shocks of failure crops. The advantages of this sector in producing crops, preparing of soil, supplying of food, employment opportunities and others benefits beyond of this (Birthal and Ali, 2005).

Labour productivity is defined as the amount of total goods and services produced by labour in an hour and growth of labour productivity the workers to produce more quantity of output for a specific number of times. There are four major determinants of labour productivity investment, investment in physical capital, new technology and human capital (Shawn Sprague). Livestock is animals like sheep, goat, horses, hens, camels, asses, cattle, cow and buffalo. They are kept on farm houses and produce sources of meat, milk, skin, hair, wool, bones, fats, eggs, hair and many other matters for crops. But in the modern age livestock field is diversified in to two sub sectors the first Dairy Farm Sector and second is Poultry Sector. In the world Pakistan’s position is 3rd in milk producing countries the most prominent ranking in milk processing and dairy products. The major contributors of milk and milk products are cows and buffaloes PES, 2014-15.

This sector produces an additional food in the form of meat, mutton, butter, milk, dry milk, cream, egg, fish, poultry, ice cream and many other products of dairy and raises the efficiency of labour productivity in rural areas. Further it encourages goods and services income of farm and poultry products caused additional employment of economy. By selling of livestock and its products they can purchase instruments and inputs like tractor, thresher, trolley, harvesters, Tube well, fertilizers, pesticide and innovative seeds which can increase not only sustainability and productivity of rural labour but also raise the productivity of agriculture sector. It also supplies organic manure, draught power and facilitates crop sector by providing hides, fibers, bones, blood and skin to the manufacturing sector. Conservation of the environment is made possible with the help of livestock sector. The supplements of livestock sector income in the form of crop production and absorb fluctuations when a crop is a failure. This sector creates a continuous stream of income and employment and minimizes seasonality in livelihood patterns particularly for the rural down trodden poor people (Birthaln et al., 2005).

Dynamics of Livestock

Diary sector

The economic survey of Pakistan 2017-18 the current statistics and the numerical statistical data of different species has emerged the cattle the most prominent population with million, the 2nd position of buffalo position at 38.8 million and sheep, goat, camel, horses, asses, mules are at 30.5, 74.1, 1.1, 0.4, and 5.3 respectively during 2017-18. The cattle species has climbed up from 36.9 million in 2011-12 to 46.1 million in 2017-18. There has been increased in the total numbers of bovine by more than 3% and the percentage increase in the population of ovine is 2.13 during 2017-18 in the country while the other livestock is smaller in growth in percentage. In milk production and consumption of the Pakistan’s position is 3rd in the world. The numerical measurement of milk production was 38690 tons in 2011-12 and 46682 tons during 2017-18. The percentage rise in production of milk has been 3.24 shown by Table 1.

Table 1: Estimated milk and meat production (000Tones)

To analyse the short-run and long-run relationship among productivity of labour per worker, livestock, human development index, gross fixed capital, inflation and governance are presented research ARDL model of equation (1) by following (Pesaran and Pesaran, 1997) and (Pesaran and Shin, 1999), as

The first step in ARDL approach to co-integration the long-run relationship among variables was checked by F-statistic.

For error correction mechanism the first Lag of the level for each variable was included in the equation (2).

Interpretation of Empirical Results

Table 3: Bound Test

Source: Author’s own calculations

The calculated value of F-statistics was 26.895 which are more than lower limit value 3.118 and upper limit value 4.557 at 95%, and lower limit value 2.578 and upper limit value 3.823 at 90 % confidence interval, confirmed the long run relationship and co- integration among variables. The above value of bound test rejects the null hypothesis (co integration does not exist among variables) and accepts the alternative hypothesis (co integration exists among variables).

The value of R2 was 0.929 suggested that 0.894 % variation in the model was the result of coefficients and the other was the result of an error term. The high value of R2 was the sign of good fit of the model while adjusted R2 was associated with degree of freedom (n-k). The value of Durbin Watson is close to 2, the sign of no autocorrelation. The error terms are not correlated with each other. The higher value F-Statistics is 26.47 confirms the overall significance of the model.

Table 4: Good Fit Model explanation

Table 5: Diagnostic Test

Source: Author’s Estimation

Auto regressive distributive lag model holds all assumptions of OLS. The assumptions of no correlation among explanatory variables, constant variance of error term and no correlation among error term should be clear for efficient modeling and these results can be used in predicting policies and formulation of policies. Auto Regressive Distributive Lag approach confirms all the assumptions of Ordinary Least Square. The Lagrange Multiplier test evaluates the absence of Serial Correlation/auto correlation and Ramsey Reset Test explains the correct functional form. When p-value of the serial correlation, the functional form, normality of LM-version and F-version is higher than 0.1 or 10%, and data is normally distributed without violation of OLS assumptions.

Table 6: Estimation of the model in long run perspective.

Source: Author’s own calculations

The long run results are the most crucial finding of the model which shows the more importance of the livestock production index in long run while the other variables GDPGR, GINI, head count ratio and FDI have most valuable coefficient in generating labour productivity in Pakistan.

The one unit increases in livestock production, raises the labour productivity by 1069 units and the one unit rises in GDPGR, expands the labor productivity by 41. 82 units while unequal distribution of income raises the labor productivity by 57 units as the poverty decline the labor productivity by 4.83. The FDI effect on labor productivity is insignificant. The livestock production index effect on labor productivity is positive and statistically significant at 1%. While the other control variable GDPGR, GINI and FDI has significant impact on labour productivity.

Brown et al. (1975) purposed stability test for confirmation structural stability of the model in short run variables as well as long run coefficients. Pesaran and Pesran (1977) employed the test practically, if Cumulative Sum of Recursive Residuals CUSUM line lies in between 5% critical bound limits and the graph of CUSUM sum of square line also lies in between 5% critical bound limits which confirms the absence of breaks of the model and confirms structural stability of the model in short run as well as long run.

Table 7: Error correction results explanation

Source: Author’s own calculations

The Error correction model analysis of regression conveys the information of short run relationship of coefficients. But here the concept of co integration and ECM becomes more important in error correction model of co integration because it resolves the short run and long run analysis incorporated with help of error correction model. In ARDL model when without stationary variables are regressed they may give spurious results. So this problem can be resolved by taking first difference of the data which confirms the stationary problem of the data. The spurious results of regression may be corrected and meaningful model will be achieved. ARDL technique is attached with unrestricted error correction model.

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