Slide 1

DEMOGRAPHIC VARIABLES AND ITS SIGNIFICANCE FOR BUSINESS ACTIVITIES

ByTadjuddin Noer Effendi

Faculty Economic and BusinissGadjah Mada University Yogyakarta 2015Why demography is need to be understood for business (peoples) or activities? Almost all private and public sector activity has the ultimate aim of producing or delivering some kind of good or service to people A necessary and fundamental preliminary to efficient and effective production and delivery of goods and services is need supporting a detailed knowledge of the population and social situationOther reasonsDemographic variables have potentiality to provide basic data and information to help in strengthening business activities and prospect of market for the future.

Demographic variables such as age structures, education and employment can determine nature of business and market situation.

Theoretically the relationship between demography demography business activities can be analysis from two perspectives

1. Demography variables place as an independent variable Demographic variables Business activities Number of population Population growth and density Population structures (Age, education, employment etc) Economic and social condition2. Demography variables place as a dependent variables

Business activities Demography Industries Number of population Services Population structures Agriculture Employment Unemployment An example for industryBatam before as an industry areas its number of population about 60.000 inhabitants. Since its as an industry areas number of population has increase in 1990 approximately 106.667, in 2000 434.299 and in 2010 949.775. Population growth in period 1990-2000 about 15.6%/year and 2000-2010 7.7%/year.

Contribution of in-migration, particularly working age population, for population growth is high. As a result, approximately 65% of population are working age population. This has an implication for business activities for serving the need of working age population.

An example for serviceYogyakarta as a centre for education and tourism also the age structures tend to higher proportion in working age population. Business activities are related to serve student facilities service or to support tourism activities

An example for agriculture

For example the implication of business activities on demography, we see from comparison between palm oil activities in Sumatera and paddy activities in Java

Palm oil activities in rural Sumatera have an implication on demography, more specifically on rural-urban migration. In North Sumatera in period 1971-1980 in-migration to urban, especially to Medan (since industrial development), were relatively higher, population growth about 8.9%/year. However since the increase of palm oil product (CPO) in international market lead to increased income of people involved in palm oil activities have reduced of rural-urban migration incident. Many young generations willing to stay in rural areas to involve in palm oil activities since it can give more better in cash income than other activities. Also many young people back in to rural areas (return migration) since palm oil products (CPO) increase. In period 1999-2000 Medan city population growth about 0.97 %/year and in period 2000-2010 0.75%/year.

On the other hand, some districts of North Sumatera that hinterland has majority of population involve in palm oil activities their population growth increase. Population growth (%/year) Districts 1990-2000* 2000-2010** Labuhan Batu 1.42 2.29 Deli Serdang 2.09 2.94 Asahan 0.58 0.85 Source, *BPS, 2000, Penduduk Indonesia: Hasil Sensus Penduduk 2000, Seri RBL1.2, Jakarta, p.172 **BPS, 2010, Penduduk Indonesia: Menurut Propinsi dan Kab/kota sensus penduduk 2010, Jakarta, p. 17-18 Paddy areas of rural JavaMany young generation of paddy areas of rural Java are likely to migrate to other areas (urban) in order to get better job and income. May be this cause of income generated from agriculture activities especially paddy tend to uncertainty and low. No doubt young generation have finished secondary level tend to leave rural areas in looking for job and better income as their aspiration that may not available in rural areas. This indication can be seen from population growth data of selected districts of rural Java.

Population growth (%/year) Districts 1990-2000* 2000-2010** Purworejo 0.04 - 0.25 Kebumen 0.37 - 0.16 Wonogiri 0.08 - 0.40 Tegal 1.11 - 0.30 Pemalang 1.27 - 0.10 Magelang 0.78 - 0.04

Source, *BPS, 2000, Penduduk Indonesia: Hasil Sensus Penduduk 2000, Seri RBL1.2, Jakarta, p.172 **BPS, 2010, Penduduk Indonesia: Menurut Propinsi dan Kab/kota sensus penduduk 2010, Jakarta, p. 17-18 Golongan umur Kulon Progo(%)Bantul(%)Gunungkidul(%)Sleman(%)Kota Yogyakarta(%)DIY(%)15-190,18 0,491,04 0,320.430,6120-240,99 3,133,92 2,052,572,8825-292,59 6,674,83 4,434,984,9630-344,7510,156,47 7,307,497,4635-396,9610,777,55 9,219,278,7440-449,4911,7010,0610,8110,7110,6145-4912,0512,2010,4511,2512,3311,3850-5412,8911,7511,2311,0413,3811,6355-5911,809,7710,7110,5712,9010,6160-64 9,556,579,23 8,17 8,698,2965-69 8,434,977,38 7,06 4,896,7270-74 8,695,037,437,27 5,096,84>=7511,636,819,7110,52 7,269,25Jumlah % 100100100100100100 N131.918261.586318.005169.12717.611898.247Angkatan Kerja Bekerja di Sektor Pertanian Menurut Golongan Umur di Kabupaten/Kota se-DIY Sumber : Kemendagri, hasil olahan data SIAK semester II 201375,33 %24,67 % FOCUS OF DISCUSSION NUMBER OF POPULATION, POPULATION DISTRIBUTION, AND POPULATION DENSITY POPULATION GROWTHPOPULATION STRUCTURES AGE EDUCATION EMPLOYMENT THEIR CHANGES OVER TIME AND IMPLICATIONS ON MARKET SITUATION AND BUSINESS ACTIVITIESNUMBERS OF POPULATION, DISTRIBUTIONS AND POPULATION DENSITYHOW WE ANALISYS THOSE VARIABLES?

To analysis those variables we need demography data For examples, we use Indonesian case and data. We can analysis by islands provinces districts sub-district Islands Male Female Total Distribution (%)Density (person/km2)Sumatera

Java

Nusa Tenggara

Kalimantan

Sulawesi

Maluku and Papua 25.629.682 (50,6%) 68.451.461 (50,1%)

6.464.872 (49,5%)

7.094.742 (51,5%)

8.670.721 (49,9%)

3.216.102 (52,0%) 24.984.265 (49.4%)

68.111.681 (49,9%)

6.602.727 (50,5%)

6.674.801 (48,5%)

8.708.677 (50,1%)

2.963.632 (48,0%) 50. 613.947 (100%)

136.563.142 (100%)

13.067.599 (100%)

13.772.543 (100%)

17.359.398 (100%)

6.179.734 (100%)

21,3

57,5

5,5

5,8

7,3

2,6 105

1.055

178

25

92

12INDONESIA119.507.580 (50,3%) 118.048.783 (49,7%) 237.556.363 (100%) 100 124Population numbers by gender, distribution, and density of main island, Indonesia, 2010Sumber: BPS, 2010, Penduduk Indonesia menurut kabupaten/kota hasil sensus 2010, Jakarta, hal. 10-11

Source of Indonesian Population Data Population census (every 10 year ) 1961, 1971, 1980, 1990, 2000, 2010Laborer Survey (Sakernas) every year since 1976Inter Census Survey (every 5 year) National Social-economic survey (Susenas) every year since 1976Rural Potentiality (Podes)Special publication (wages, consumption index others)

BPS sometime use similar concept but different definition . We need to check the definition before we comparing the data.

POPULATION GROWTHPopulation growth can be used for basic information in investment planning. It can give us information about existing, and prospect of population (potential market) in the future.

Factors determine the low of population growth.1. The decline of fertility rate in few provinces are caused of some factors namely:

Social change, especially female education has increased and female has initiated to enter the labor market of public sectors in order to get wages. This brings change in social (life) behavior of women, especially towards marriage. They tend to delay marriage since they have to finish education for the sake of their career development in work place. For the married women, planning spacing of pregnancy is becoming a norm and the preference to have children depend on the family economic condition. Two children have already been a norm in young families. The awareness in birth control have spread out and have already been accepted in the societyThe first age marriage have increased significantly, especially for young generations followed with young eligible couplesSmall family norm are starting to be accepted and children are seen to be an economic burden (not as fortune any more)Service towards the effort to controlling and delaying pregnancy are available and easy to find.

2. The decline of mortality rate is caused from several factors namely:

Prevention for infection and spread disease has improved significantly. People are already free from the spread diseases. Primary health care had developed and spread out so that people have easy access to find the health services. Access to service for pregnancy, childbirth, and modern facilities for mother, baby and child are already easy to find. Incidence of poverty tended to decline and family health nutrition had been improved and nutrition for child under five years has improved significantly.Life expectancy for all age has increased.

IndicatorsLive expectancy (year) 1996* 2011**

Infant mortality (o/oo) 1970*** 2010****

% of poor people***** Urban 2007 2011 Rural 2007 201164.470.9

104 26.8

12.5 9.8

20.4 16.6

Selected Welfare Indicators lSources: BPS, Bapenas, UNDP, 2001, Indonesia Human Development Report 2001: Towards A New Concensus, Jakarta, p.78** BPS, 2011, Perkembangan Beberapa Indikator Utama Sosial-ekonomi Indonesia, May 2011, Jakarta, p.36 ***World Development Report, 1991, Investing in Health, Washington, p.59**** BPS, 2010, Perkembangan Beberapa Indikator Utama Sosial-ekonomi Indonesia, August 2010, Jakarta, p.16 ***** BPS, 2010, Perkembangan Beberapa Indikator Utama Sosial-ekonomi Indonesia, May 2011, Jakarta, p.39

Indonesian Population in the futureEach year population increase 1.49% or about 4 million. In 2050 number of population will reach about 350 millionIn Java number of population about 210 million or about 60% of Indonesian population. Population life in urban areas about 60%

POPULATION STRUCTURESAgeEducationEmployment Age Population growth both caused by fertility or in and out /in migration would affect the age of population structures.

Year

Implication the change of age structures Dependency ratio decrease

Age productive (15 60 ) increase Age non productive (0-14) decline Old population (>65) increase but still low This demograhic situation called as DEMOGRAPIC BONUS or DEMOGRAPHIC DEVIDEN led to decline in dependency ratio Demographic bonus can stimulate economic growth Social cost for age groups 0-10 decrase The cost can be shifted for saving and investation purchasing power increase middle class growing market expansion Demographic bonus occurred only ones in demographic history of a nation Total dependency Child dependency Old dependency Economic support ratio ratio ratio ratio Countries 2000 2025 2050 2000 2025 2050 2000 2025 2050 2000 2025 2050Japan 0.468 0.673 0.838 0.217 0.226 0.254 0.250 0.447 0.583 0.637 0.582 0.545South Korea 0.393 0.477 0.678 0.299 0.252 0.270 0.094 0.226 0.417 0.647 0.622 0.564 Indonesia 0.546 0.456 0.573 0.473 0.333 0.313 0.073 0.123 0.260 0.683 0.695 0.652Philippines 0.676 0.458 0.521 0.615 0.353 0.305 0.061 0.105 0.216 0.677 0.672 0.649Thailand 0.450 0.453 0.660 0.366 0.274 0.278 0.084 0.178 0.382 0.787 0.728 0.653Bangladesh 0.622 0.428 0.523 0.569 0.344 0.309 0.052 0.084 0.213 0.753 0.761 0.728India 0.620 0.459 0.531 0.540 0.336 0.300 0.081 0.123 0.232 0.641 0.638 0.601Table 3economic ratios, selected Asian Countries, 2000, 2025 and 2050Source: Mason, Lee and Russo (quoted in, p.310)Summary of dependency and economic ratios, selected Asian Countries, 2000, 2025 and 2050

Source: Mason, Lee and Russo (quoted in Basri, 2012, p.310)QTotal dependency ratio (10 -14) + ( 65 over) -------------------------- x 100 (15 - 64)

Child dependency ratio (0 - 14) ---------- x 100 (15 - 64)

Old dependency ratio 65 and over ------------------ x 100 (15 - 64)Year Total Young old 71.7 62.6 9.11925 71.8 63.0 8.81930 70.5 62.3 8.21935 71.1 63.1 8.0 68.9 61.0 7.9 67.8 59.5 8.3 63.6 54.9 8.7 1960 56.1 47.2 9.0 47.5 38.2 9.2 45.1 34.9 10.3 47.7 36.0 11.7 1980 48.2 34.9 13.3 Dependency ratio in Japan 1920-1980atio in Japan 1920-1980Source: Okita, Saburo and Kuroda, Toshio, 1981, Japan s Three Transitions, Series 1, Tokyo, Nihon University Population Reseacrh Institute

Age structures and consumptionThe areas where demographic analysis may be most helpful to businessman are:

It can help in identification the location of potential market.it can help in understanding the behavior of the diverse consumer groups that make up markets for goods and services both for existing situation and for the future.

FIGURE 1 Australia: Average Weekly Household Expenditure on Selected Items by Age, 1988Source: Hugo, Graeme, 1981, p. 8

Source: Hugo, Graeme, 1981, p. 9FIGURE 2 United States: Expenditure on Selected Items by Age, 1988

Source: Hugo, Graeme, 1981, p. 9

EDUCATION

Education is one important information for business activity especially for investors. Information on population education structure of a region could give a picture of the skill formation of the labors that are needed to support business activities.The region with low population education maybe less attractive for business activities which needs support from skilled labors. For business activities that do not need unskilled labors the low education structure would not be a problem but the level of wage would still be in consideration. Usually educated skill labors require different wages from unskilled labors. Business activities that are trying to find low wage levels usually look for regions with low population education structures.

Education continueEducation in a normal condition could also be used as an indicator for the economic status of a population. Regions with a relatively high population education structure tend to have high incomes. Because of that it could also be used as proxy purchasing power of population.

The lifestyle of the population is affected by education. Based on those reasons, the need for goods and services for the population with better education is different from uneducated.

Provinces Education (%) 1990* Education (%) 2010** Primary Secondary Tertiary Primary Secondary TertiaryAcheNorth SumatraWest SumatraRiauJambiSouth SumatraBengkuluLampungBangka BelitungKepulauan RiauDKI Jakarta West JavaCentral JavaYogyakartaEast JavaBantenBaliWest NusaTenggaraEast Nusa TenggaraWest KalimantanCentral KalimantanSouth KalimantanEast KalimantanNorth SulawesiCentral SulawesiSouth SulawesiSoutheast SulawesiWest SulawesiGorontaloMalukuMaluku UtaraWest PapuaPapuaINDONESIA73.269.872.175.878.379.176.881.7--51.980.983.067.781.2-75.684.586.283.776.378.269.271.278.076.777.8--74.9--79.673.425.428.726.122.820.519.821.517.5--42.817.816.029.417.6-22.414.512.815.322.620.628.526.920.621.520.8--23.7--19,022.31.41.51.81.41.21.11.60.8--5.31.31.02.91.2-2.01.01.01.01.11.22.31.91.11.81.4--1.4--1.41.647.946.550.950.956.658.353.756.760.639.130.857.761.642.660.351.750.964.468.064.457.758.646.448.157.756.266.163.763.149.354.145.163.655.744.247.642.343.538.736.439.839.834.852.955.337.233.547.034.941.639.930.827.431.736.335.746.345.036.336.429.831.732.143.740.245.631.338.37.95.96.85.65.25.36.54.04.68.0 13.95.84.910.44.87.79.24.44.63.96.05.77.36.96.27.44.14.64.87.05.l79.35.16.0Table 4Education Structures of Population by Province in 1990 and 2010

Source: *BPS, 1992, Population of Indonesia: Result of Census 1990, Seri S2, p.141 **BPS, 2011, Welfare Statistics 2010, Jakarta, p.89

Employment

Besides education as discussed in the previous section, labor force and employment data could also be use as an indicator to examine the social and economic transformation process of a region.

Provinces 1990* 2010**Labor Force Participation Rate (%)Open Unemployment Rate (%)Labor Force Participation Rate (%)Open Unemployment Rate (%)AcehNorth SumatraWest SumatraRiauJambiSouth SumatraBengkuluLampungBangka BelitungRiau IslandDKI JakartaWest JavaCentral JavaYogyakartaEast JavaBantenBaliWest Nusa TenggaraEast Nusa TenggaraWest KalimantanCentral KalimantanSouth KalimantanEast KalimantanNorth SulawesiCentral SulawesiSouth SulawesiSoutheast SulawesiGorontaloWest SulawesiMalukuNorth MalukuWest PapuaPapua

INDONESIA53,253,951,053,256,654,959,556,8--48,749,758,663,457,3-61,759,263,261,258,757,853,651,354,544,153,5--49,6--60,92,83,23,02,81,92,91,81,9--7,14,12,62,52,7-2,02,20,81,91,83,34,34,32,74,83,3--3,4--3,163.269.566.463.765.870.271.967.966.568.867.862.470.669.869.165.377.466.672.873.269.971.366.463.369.264.171.964.471.566.565.169.380.9

67.78.37.46.98.75.96.64.65.64.66.911.010.36.25.74.313.73.15.33.34.64.15.210.19.65.28.44.65.24.610.06.07.73.5

7.1Table 5 Labor Force Participation and Open Unemployment Rate by provinces 1990 and 2010

Labor Force Participation Rate and Open Unemployment by provinces 1990 and 2010

Labor Force Participation Rate and Open Unemployment by provinces 1990 and 2010Source: *BPS, 1992, Populations of Indonesia: Result of Census 1990, Jakarta, Seri S2, p.267 **BPS, 2011, Welfare Indicators 2010, Jakarta, p. 201

Source : BPS, 2011, Laborer Situation, Agust 2010, Jakarta, p. 25, 26, and 27

Province 1990 (%)* 2010 (%)**AgricultureIndustryServicesAgricultureIndustryServicesAcehNorth SumatraWest SumatraRiauJambiSouth SumatraBengkuluLampung Bangka BelitungRiau IslandDKI JakartaWest JavaCentral JavaYogyakartaEast JavaBantenBaliWest NusaTenggaraEast Nusa TenggaraWest KalimantanCentral KalimantanSouth KalimantanEast KalimantanNorth SulawesiCentral SulawesiSouth SulawesiSoutheast SulawesiGorontaloWest SulawesiMalukuNorth MalukuWest PapuaPapua65.560.459.858.169.764.570.970.2--1.136.847.945.550.1-44.154.375.272.561.953.843.255.767.557.668.0--62.0--71.98.910.49.213.18.110.46.48.7--28.123.219.419.416.4-21.516.912.28.115.214.620.513.08.810.17.8--11.4--6.925.629.231.028.822.225.122.721.1--70.840.032.735.133.5-34.428.812.619.422.931.636.331.323.732.324.2--31.3--21.252.246.944.947.757.360.462.061.532.713.11.024.739.233.744.719.031.253.068.562.657.243.129.335.258.951.152.142.663.751.654.0 47.1 75.2 9.212.211.011.49.08.26.28.630.238.821.625.122.117.416.930.219.411.38.29.411.215.121.014.27.510.210.411.07.97.08.310.5 4.338.641.044.140.933.731.431.829.937.148.177.450.238.948.938.450.849.435.723.328.031.641.849.750.633.638.737.546.428.441.437.742.420.5Indonesia 40.5 17.6 41.9 Source: *BPS, 1992, Population of Indonesia: Result of Census 1990, Jakarta, Seri S2, p.312 **BPS, 2011, Ketenagakerjaan Penduduk Indonesia: Hasil Sensus Penduduk 2010, Jakarta, p.48, 49 , 50 and 51Percentage of Population 10 Years and over Worked During The previous Week by Industry and Province in 1990 and 2010

Conclusion Demography variables need to be consider in analysis of potential, in expansion of market and in developing bussiness activities

Writing individual paper

Topic : Relationship between business activities and demographic variables as a dependence or an independence

Length : Maximum 5 pages (not including cover, references and attachments

Writing in font type new time roman ,font 12, and spacing 1.5

In analyzing only looking at OT (opportunity and threat)

Time: regular 2 weeks non-regular 4 weeks

Chart10.439.41446.20.339.616.943.33.840.217.238.84.54417.933.65.648.41928.8

Age groups>6525-6415-240-14PersentaseIndonesian population by age group in period1970-2010

Sheet1>6525-6415-240-1419700.439.41446.219800.339.616.943.319903.840.217.238.820004.54417.933.620105.648.41928.8To resize chart data range, drag lower right corner of range.

Implikasi peningkatan pdkk usia lanjut di DIY Komposisi penduduk menurut umur, gender DIYLanjut usia terlantar di Kabupaten se DIY L P TotalSleman 1.809 4.480 6.289Gunungkidul 4 .269 10.58214.851Kulon Progo 1.718 3.833 5.551Bantul 2.330 5.646 7.976 Kota Yogyakarta 576 1485 2.061 10.702 26.02636.728 Sumber: Dinas Sosial DIY 2013

Proporsi penduduk usia ( >65) terhadap pddk DIY =360651/ 3.561.448X100= 10,125% Jumlah penduduk miskin menurut BPS (www.bps.go.id) Maret 2014 (544.870) atau 15,0% Penduduk lanjut usia terlantar terhadap penduduk miskin 36.728/544.870x100=6,7%Golongan umurJumlah Penduduk 0 4 229.592 5 9 255.660 10 14 264.027 15 19 254.029 20 24 252.682 25 29 251.976 30 34 289.823 35 39 277.010 40 44 279.669 45 49 263.674 50 54 238.133 55 59 199.321 60 64 145.201 65 69 110.328 70 74360651 104.832 >=75 145.491 Jumlah 3.561.448 Attachment 1

Population Projection by age

To do population projection by age we can use formula:

1. Geometric method

t

Pt = Po ( 1+ R) Pt =Numbers of population in year t

Po =Numbers of population in year 0

R =Population growth

t =time reference

2. Exponential method

rt

Pt = Po e

e = 2.7183

3. Life Tables Model

For example see Table below

Hypothetic Population Projection for Female by Age 2010Age groups No.of Population

In 2005 P (x)*Population Projection

In 2010**

0 - 4

5 - 9

10 - 14

15 - 19

20 - 24

25 - 29

30 - 34

35 - 39

40 - 44

45 - 49

50 - 54

55 - 59

60 - 64

65 - 69

70 74

75+ 20,985

23,223

21,482

18,926

16,128

15,623

13,245

11,184

8,081

7,565

6,687

4,831

4,526

2,749

2,029

1,972 0.98459

0.99427

0.99321

0.99032

0.98787

0.98581

0.98321

0.97945

0.97351

0.96355

0.94812

0.92314

0.88220

0.81710

0.71400

0.58313

20,661

23,090

21,336

18,742

15,932

15,401

13,022

10,954

7,866

7,289

6,340

4,459

3,992

2,246

1,448

*Value of Px available in Life Tables Model

**The result of population projection in 2005 is no.of population in 2000 mutiple by Px.

Population 0-4 in 2000 become 5-9 in 2005

Chart121.44.17.123.46.29.419.72.65.5

Age groupsAge 15-24Age 25-65TotalPercentageFigure 4Open Unemployment Rate by Age Groups 15-24 and 25-65in Urban dan Rural, Indonesia, Year 2010

Sheet1Tingkat Pengangguran Terbuka Menurut Umur 15-24 dan 25-60 di Perkotaan dan Pedesaan, IndonesiaAge 15-24Age 25-65TotalIndonesia21.44.17.1Urban23.46.29.4Rural19.72.65.5To resize chart data range, drag lower right corner of range.

Sheet2