ESTIMATION OF LIFE EXPECTANCY AT BIRTH

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1 CHAPTER V ESTIMATION OF LIFE EXPECTANCY AT BIRTH 5.1 Introduction Life expectancy at birth (e 0 0) is one of the most preferred indicators in demographic and health analysis. Life expectancy at birth reflects the average number of years a new born baby is expected to survive under the current schedule of mortality. It is a proxy measure for several dimensions like adequate nutrition, good health, education and other valued achievements. Besides, life expectancy at birth is used in the construction of a dimensional index of health in Human Development Index (HDI) and Gender Development Index (GDI). Hence, in formulating the National/Subnational Human development reports the estimates of life expectancy at birth are largely required. As discussed in the first chapter, reliable estimates of life expectancy at birth at the national and sub national levels (major states) are available from SRS. However, the availability of reliable estimates for smaller states and districts of is scanty. In this chapter we attempt to provide some methods to estimate life expectancy at birth for smaller states of. We also attempt to provide the estimates of and e 0 0 for the districts of. 5.2 Estimation of Life Expectancy at Birth The estimation of life expectancy at birth is usually provided by the RGI using the data of SRS for major states of. These estimates are provided for a period of five years, say , and published in the SRS Abridge Life Tables. These estimates are derived using the clubbed data for five years of ASDR. The estimates for the period may be referred to the mid period, i.e.,. However, the estimates of life expectancy at birth are usually not provided for smaller states of as well as the districts of. Here it is attempted to provide the life expectancy at birth for the followings. 51

2 a. Smaller states of for the period using the regression method b. Districts of for the period 2001 using the regression method The estimated value of life expectancy at birth, as provided in SRS based abridged life tables is given in table 5.1 and table 5.2. Table 5.1 shows the estimated life expectancy at birth during , mid year of which is 1990, whereas table 5.2 shows the same for. This is given for major states of and by place of residence and sex. It is observed that the level of life expectancy varies across the states of as well as by place of residence. In most of the states life expectancy at birth for females is higher than that for males. Similarly, life expectancy in urban areas is substantially higher than in rural areas. Table 5.1: Life expectancy at birth by sex and residence, and states, Total Rural Urban /States Total Male Female Total Male Female Total Male Female Andhra Pradesh Assam Bihar Gujarat Haryana Himachal Pradesh Karnataka Kerala Madhya Pradesh Maharashtra Orissa Punjab Rajasthan Tamil Nadu Uttar Pradesh West Bengal

3 Table 5.2: Life expectancy at birth by sex and residence, and states, /States Total Rural Urban Total Male Female Total Male Female Total Male Female Andhra Pradesh Assam Bihar Gujarat Haryana Himachal Pradesh Karnataka Kerala Madhya Pradesh Maharashtra Orissa Punjab Rajasthan Tamil Nadu Uttar Pradesh West Bengal Source: SRS based Abridged Life table, Table 5.3: Annual change in life expectancy at birth in and states, Total Rural Urban /States Total Male Female Total Male Female Total Male Female Andhra Pradesh Assam Bihar Gujarat Haryana Himachal Pradesh Karnataka Kerala Madhya Pradesh Maharashtra Orissa Punjab Rajasthan Tamil Nadu Uttar Pradesh West Bengal Source: SRS based Abridged Life table,

4 According to SRS estimates (), the states on the ascending order of longevity for are: Madhya Pradesh, Assam, Orissa, Uttar Pradesh, Bihar, Gujarat, West Bengal, Karnataka, Tamil Nadu, Haryana, Maharashtra, Punjab and Kerala (Table 5.2). Table 5.3 shows the change in life expectancy at birth for both males and females by place of residence. The basic idea is to observe the change in the life expectancy at birth in 1990s. It is observed that life expectancy at birth had increased from 58.7 years in 1990 to 62.5 years in. In other words, life expectancy at birth had increased by 3.8 years during this period, a gain of about 0.38 years annually. The increase is 0.30 years for males compared to 0.43 for females in the country. This is an indication that there has been an improvement in the mortality situation in the country for both males and females. A similar differential is also observed for states of but the pace of increase varies substantially. 5.3 Estimation of Life Expectancy at Birth for Smaller States of The estimates of life expectancy at birth are not provided by SRS for smaller states of. Accordingly, it is attempted to provide the estimates for the smaller states of using indirect techniques. The regression equation is mainly used for providing such estimates. In deriving the estimates, it is assumed that the is closely linked to life expectancy at birth. Accordingly, the relationship of and life expectancy is established by taking the SRS data for the major states of. Accordingly, two sets of regression equation (one linear and one quadratic) have been attempted by taking life expectancy at birth as the dependent variable and as the independent variable over three different time periods. The description of methodology with result is given below. Linear Regression Method: We have used a linear regression method with life expectancy at birth as the dependent variable and as the independent variable for the major states and for the year of, 1995 and We have pooled the data for rural and urban areas and for males and females. Life expectancy at birth is regressed against and the coefficients are obtained. These variables ( and life expectancy at birth) are actually observed values for the major states of. 54

5 Regression equation: Dependent Variable: Life expectancy at birth (at state level) Independent Variable: (at state level) Method: OLS Regression Equation: LEB = a+ b* LEB 1995 = a + b* 1995 LEB 1991 = a + b * 1991 where a and b are the regression coefficients. Quadric Equation: We have also fitted a quadric model to examine the improvement against the linear regression. The equation is of the form: LEB =a + b* + c* 2 Similar equations are also used for 1995 and The result obtained from both the methods as well as the fitting of the curve is discussed below: Table 5.4: Results of the OLS and Quadric equation Methods OLS Quadric Intercept Regression coefficient () Regression coefficient ( 2 ) R F Statistics N Unit Comments The second coefficient of quadric equation is not significant Almost same R 2 Model is significant in both cases From the regression results the following inferences may be made: The coefficient (OLS) is stable over the period i.e. 1991, 1995, and. The value of R 2 is high. The coefficients as well as the regression model are significant. The OLS regression is preferred as compared to quadratic as the coefficient in quadratic equation is not significant. 55

6 The regression coefficient is used for providing the estimates for the smaller states of and districts of. The used in the table 5.4 are obtained from SRS Bulletin. We preferred to use the three year moving average to avoid fluctuation in due to small sample size. Wherever data for the period of 1999, and 2001 are not available, suitable adjustment has been done and specified in the footnote. However the value of e 0 0 depends on the estimates of. Estimation of Life Expectation at Birth in : The estimates of life expectancy at birth for smaller states of is based on the following regression equation = * where is the slope and is the intercept term. It may be mentioned that the estimates of for the smaller states of are obtained from the various SRS bulletin. However, for most of the states, we have taken the estimates of as the moving average of 1999, and The mid period of which is the year. However, there was some flexibility in following states due to non availability of data at all the three periods. The following adjustments are made to provide the estimates of life expectancy at birth for the smaller states of. Andaman & Nicobar Island: The estimates of are not available for urban areas (male) for the period of 1999, and It is only available for the year. So it is stated as the average for the urban male of this UT. Arunachal Pradesh: For urban areas and for urban females two year moving average had been prepared because of non-availability of for the year For urban males the average had not been prepared due to non-availability of for all three years. Chandigarh: for 1999 is not available, so a two-year moving average has been made by taking the estimates of and

7 Dadar & Nagar Haveli: Due to non-availability of for total urban area and also for urban females for the year 1999, a two years moving average has been taken (average of of & 2001). For urban males of is only available so this value is stated as the moving average. Daman & Diu: For total urban area and for urban females only and 2001 is available, so for this state a two year moving average had been prepared, but though the for urban males is not available the moving average for this category had not been prepared. Goa: Due to non-availability of 1999, the two year moving average had been taken for urban males and females. Jammu & Kashmir: For this state the is not available for 1999, so the moving average has been derived on the basis of two year of and Lakshadweep: for urban males only 2001 is available so the figure is only stated as the moving average. Mizoram: 1999 for urban males is not available so the two-year moving average has been prepared for the state. Nagaland: For this state the of 1999 is only available for total and rural areas, but for urban area only the female is not available for 2001 Pondicherry: 1999 is not available for urban females so the moving average has been prepared by the of and Sikkim: for urban females only 2001 is available so the moving average for the category is stated as the of Uttaranchal: for 2001 of urban males is not available so the two-year moving average of the of 1999 and had been taken. And for urban females only 2001 is available so the figure of that has only been stated as the moving average. 57

8 Table 5.5: Estimation of life expectation at birth for the smaller states of, (Derived from regression equation) State Total Rural Urban Total Male Female Total Male Female Total Male Female Arunachal Pradesh * ** Chhatishgarh Goa Jharkkhand Himachal Pradesh J&K Manipur Meghalaya Mizoram Nagaland NA ** NA ** NA ** NA ** NA ** NA ** Sikkim *** 67.4 Tripura Uttaranchal *** 69.0 A&N Chandigarh Dadar&Near Haveli Daman &Diu * ** Delhi Lakshdweep * ** Pondicheri *Inadequate sample to provide estimate (for the states of Arunachal Pradesh and Lakshadweep (Urban Male); Daman & Diu for (Urban female)) ** Data () is not available to provide estimate (for states of Nagaland both Total and Rural), *** Data has been taken from SRS Bulletin April 2004 (for the states of Sikkim and Uttaranchal for Urban Female), The estimates of is the moving average of 1999, and 2001 barring a few states. Source- SRS Bulletin April

9 5.4 Estimation of Life Expectancy at Birth for Districts of The estimates of life expectancy at birth are also provided for the districts of. We have use the same regression equation as discussed before for the year. The estimates are dependent on the estimates of for the districts of. If the estimates of are stable it is likely that the estimates of life expectancy at birth will be stable. The regression equation used for estimation of life expectancy at birth for 1991 is = The estimates of 1991 by RGI are used for deriving the life expectancy at birth. For the year the regression equation used is = * The district level estimates of life expectancy at birth are high if level is low and life expectancy at birth will be high if is high. However, during the expert committee meeting it was suggested that the component of adult mortality should also be included in the regression model to capture the increase in adult mortality in recent years. We could not include adult mortality as the data availability is the main constraint. In any future exercise the component of adult mortality should be included to improve the accuracy of the estimates. Based on this regression equation, the estimates of life expectancy at birth for the year 1991 and 2001 are given in Appendix B. 59

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