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CHAPTER FOUR

DISCUSSION OF FINDINGS

 4.0 Introduction

This chapter presents the data analyzed from secondary data sources on the times series analysis of milk production in Uganda. A case study of sameer agriculture and livestock limited 2014-2016. The data was tabulated to give a meaningful presentation and interpretation. Presentation and interpretation were based on the specific objectives to address the research problem.

This section further reports the estimates for milk production in Uganda function. In order to detect the long-run co-movement among the variables, the cointegration procedure developed by Johansen (1991) and Juselius (1990) was employed. An error correlation model for the determinants of milk production in Uganda was used.

4.1. Histogram Normality Test

A regression was run and on clicking on the view-residual test-histogram-normality test, the histogram is bell-shaped, suggesting a normal curve shape, and the jarque-bera statistics has high p-value of 0.558725 indicating that the errors in the regression are normal that is to say; the Jarque-bera statistics probability of 0.558725 is greater than zero and it has a percentage of 55% greater than 10%(55%>10%) thus the errors in the regression are normal.

4.1.2 Test for omitted variables

Chow Breakpoint Test

The null hypothesis is rejected and we conclude that there is a structural break inthe data.

 Distribution of milk production

The graph above shows that milk production in Uganda has been constantly changing however there is a general; decline in milk production as presented by the graph.

4.1.3 UNIT ROOT TEST

H₀   the series are stationary

Unit root tests were carried out using the augmented Dickey-Fuller test statistic. This was carried out to check whether the series were stationary (integrated) or not. This is because standard inference procedures do not apply to regressions which contain an integrated dependent variable or integrated regressors. The test statistic tested the null hypothesis that the time series has a unit root against the alternative that there is no unit root. The test statistic values are compared to the critical values at five percent significant level. The test statistic values less than the critical values at five percent level of significance indicate that the series are non-stationary otherwise they are stationary.

In the table 4, the milk production D(SER01) is not stationary in the levels and after the first difference since there ADF statistic are lower than the critical values.

The findings indicates that the durbin-watson prob(f-statistic)= (0.093822)>0.05, therefore reject the null hypothesis, therefore the series are not stationary.

TREND

COIN INTERGRATION

The next attempt involved testing the residuals for the order of integration. The application of the Augmented Dickey Fuller test statistic revealed that the residuals are stationary in levels.

Table 5: Cointegration tests output

Among the variables that are integrated of order 1(1), an attempt was made to check whether Cointegration holds. The purpose of the Cointegration tests was to determine whether a linear combination of a group of non-stationary series is stationary. Engle and Granger (1987) pointed out that a linear combination of two or more non- stationary series may be stationary.

H₀   There is no linear deterministic trend in milk production

The null hypothesis that there is no linear deterministic trend in milk production is accepted at 5% significance level.

4.1.2 Regression Analysis

Forecast 2017

The results in the table indicates that

From the figure above shows that milk production in Uganda started to decline from January to April 2016 production was declining while there is a slightly improvement in June 2017 to September 2017 while the milk production  generally decline from November 2017 to December 2017.

This implies that milk production in the year 2017 is general low as compared to previous years of 2016 and 2015. It also further indicates that the government needs to increase milk production in Uganda.

CHAPTER FIVE

SUMMARY, CONCLUSION AND RECOMMENDATIONS

5.0 Introduction

From the results its is evident that production of milk in both years of 2016 are slighlt similar however the production of milk has been reducing in 2016 while the production in 2016 was extremely low in 2017.

The study also recommends that government should get involved in measures which increase milk production some of these measure include using modern systems to increase milk production in the milk production areas , this is because there has been a declining trend of milkn production in Uganda which has costed most of the milk producers in Uganda this is also in line with  (Matthewman, 1993) who  states that in Uganda most of the cattle are found in the cattle corridor and milk is produced from cattle and goats. Dairy production systems in Uganda have been classified into three groups; pastoral, small-scale crop and livestock farms and specialized dairy farms , this types of milk production in Uganda which is mostly pastoral has affected m8ilk production this is because milk production in Uganda depends so much on nature.

While during drought period milk production is low because of low water consumption this is generally evidenced by the fact that milk production has been on the decline mainly from 2017.

The study shows that milk production in 2015 was not the same as 2016 and there has been also a general decline in the previous this shows that there needs to be an intervention this is also in line with (Okwenye, 1994) this means that proper feeding of cattle is necessary to enable the milk production to be high.

The results in the study indicates that milk production in Uganda has not been constant and therefore the years in 2015 and 2016 the trend in  milk production has been varying , the figure further shows that milk production in January was the highest and milk production in 2015 was high again months of may and June however milk production in Uganda was lower in February 2015 and march this view is also shared by (FAO, 1992; Okwenye, 1994) who indicate that

Milk production in the country takes place in regions referred to as milk shades (regions with high concentration of dairy animals) and these areas extend from just below 1° latitude in the north to Kabale in the south and from Mbale in the east to Kabarole in the west. Uganda is divided into five milk regions/sheds; southwestern, central, western, northern, and eastern. There are differences in the milk sheds in terms of the economic importance of the dairy industry to the region, herd population and production levels, farm size, grazing systems, practices, and cattle breeds used for milk production , however Karamoja zone is sometimes referred to as a separate milk shade.

The study shows that milk production in Uganda has been facing constant changes in Uganda and therefore the government needs to develop an intervention policy this is shown by the fact that milk production in 2016 was slightly lower than that of 2016, however production in 2016 was high in February 2016 up to may 2016 then milk production began to decline production began to fall from June 2016 up to august 2016 it was a continuous decline this shows that there has been a general decline in milk production and therefore there needs an intervention to ensure that there is an increase in milk production.

5.1 Conclusion

Milk production in Uganda has been declining and there is need for the government to support the farmers in ensuring the output in increased.

The level of milk production in Uganda has also shown that there needs to be an increase in the investments by the government.

The government needs to support cattle keepers with modern milk systems to enable milk production to increase.

5.2 Recommendation

Milk producers in Uganda need to be educated by the professionals on the best ways of increasing their milk output.

There needs to be government support to the farmers.