unemployment and labour force

The part of Indonesia contains 33 provinces which is divided into three regions; west, central, and east. This is a labour market with a relatively high unemployment rate and a relatively low labour force participation rate. Another feature of the labour market in the east of Indonesia is a lower educational level. There is a relatively low demand of individuals who have received higher education. Highly-educated individuals will withdraw from the region. The development of employment is an important indicator of the labour market (SEAN 2003). Vermeulen (2005) explains that regional labour markets can exist, because migration is costly for labour and capital.

A high unemployment rate is costly to the community. For instance, if there are many unemployed workers, more money is needed to pay for the social security system. Therefore, an economic policy aimed at increasing the labour force participation rate has several economic and social benefits. An important benefit of a higher labour force participation rate and a lower unemployment rate is that the costs of the social security system will be reduced.

It is therefore interesting to know how labour force participation and unemployment will develop in the future.

This post investigates how employment and unemployment will develop in the period 2010-2030 in three different scenarios. These scenarios are: quick recovery, double dip and the new common. The quick recovery scenario contains an autonomous employment growth path of 1.75 percent. The second scenario, double dip, contains a second economic dip in 2011. After this dip, the economy will improve slowly to an autonomous employment growth path of 1.75 percent annually. The last scenario, new common, assumes that after 2009, there is a small improvement of the economy after 2009 and it expects a lower autonomous employment growth path, namely one percent per annum.

In reality, labour force participation will decrease if unemployment increases. This is for example due to the discouraged worker effect. This means that disappointed job seekers leave the labour market. Because the disappointed job seeker is not longer part of the active working force, the individual drops out of the unemployment rate and thus the labour force participation rate will decrease. Several authors, for instance Fleisher and Rhodes (1976) and

Elmeskov and Pichelmann (1993), describe this negative relationship between unemployment rate and labour force participation rate.

This post will use the three scenarios described above of employment growth and investigates what the effects are of an endogenous labour force participation rate on unemployment and labour force participation. We use the model of Blanchard and Katz (1992) and argue that these simulations represent more realistic expectations.

Future expectations of labour force participation

Indonesian government has developed ambitious targets for labour force participation within the country. For 2020, the Government wants to realize an overall participation rate of 75 percent for the entire country. Indonesian government wants to realize these targets through a higher participation of women, of elderly people and a better integration of migrants in the labour market. In general, the labour force participation rate of these groups is below the average labour force participation rate.

The 75 percent target is in line with the expectations for Indonesia. Government expects that labour force participation rate will increase to 75 percent in 2014. After 2014, the labour force participation rate will be constant. We assume that economic policy does not change, so that future adjustments in the participation are caused by (1) the effect of earlier chosen policies, (2) the growth of labour force participation of women and through (3) changing in demography.

Social policies have chosen earlier strongly influence the development of labour supply in the future. The two most important policy effects are: (1) the cancelling of the possibilities to retire prematurely, and (2) a revision of the prerequisites for invalidity insurance benefits. Through this change in policy, the number of individuals assumed to be incapable to work will diminish. These policy decisions therefore lead to an increase in labour force participation.

The growth of labour force participation among women springs from two causes. First, older cohorts of women are replaced by younger cohorts. Since younger cohorts of women have higher participation rates than older cohorts, participation increases. Secondly, there is a trend that younger cohorts participate more in the labour market than the same cohorts did in previous years. It is expected that this cultural trend will persist in the following years.

Demography influences the labour force participation rate when the relative size of population groups changes. There is an inverse U-shaped relationship between age and labour force participation rate. For example, ageing leads to a lower participation rate, because in general elderly individuals will participate less than younger individuals. Moreover, younger individuals will follow education when there is high rate of unemployment (Elhorst 2008).

Three scenarios of employment growth

Demand shocks

This post uses the model of Blanchard and Katz (1992) to simulate the unemployment rate, the labour force participation rate and the employment growth rate simultaneously in the period 2010-2030. The advantage of such a simultaneous model is that the effect of every exogenous variable can be determined on every endogenous variable; so with a demand shock, it is possible to analyze what the effects are for the unemployment rate and the labour participation rate. According to Armstrong and Taylor (2000) a positive demand shock leads to an increase in employment. This increase in employment implies that new jobs must be filled by unemployed workers; therefore the unemployment rate will be reduced.

For a specific region, the rise in employment has two effects. First, the employment growth will lead to a growth in the real wages which will lead to net migration into the region and also to an increase in the labour force participation rate.

A second effect of higher employment is that the regional income of households will increase. An increase in households’ income means that there is more money available for consumption. The demand for consumption goods will thus also increase. Hence, the demand for output in the region will increase, which leads as well to an increase in employment.

Broersma and Van Dijk (2001) present the effects of a positive regional labour demand shock in Indonesian labour market. They find that in the north, unemployment will mainly absorb the shock in the short run. An increase in the labour force participation, however, will absorb the biggest part of the long run effects of this shock. This long run effect is even higher than the share of migration and unemployment. This can be explained by a relatively high unemployment rate in the eastern part of Indonesia. The underlying argument is that through relatively high unemployment rate, jobs can be filled relatively easily by unemployed workers. Broersma and Van Dijk (2001) also observe an adjustment speed of three to five years. This adjustment speed is high in comparison with other regions of Indonesia. A higher adjustment speed means that the labour market is more flexible because the labour market needs less time to adjust to a demand shock.

The scenarios

The paper of Schudde et al. (2010) computes what happens to unemployment and employment growth in three different scenarios. These scenarios are: quick recovery, double dip and the new common. The quick recovery scenario contains an autonomous employment growth path of 1.75 percent. The scenario double dip contains a second dip of three percent in

2011. After this dip, the economy will improve slowly to an autonomous employment growth path of 1.75 percent annually. The new common scenario contains a small improvement of the economy in 2010, so an employment growth of a half percent is assumed. After 2010, there will be an autonomous employment growth path, namely one percent per annum.

From the first scenario, quick recovery, the unemployment rate will achieve the highest value of 7.41 percent in 2011. After this year, employment will increase and the unemployment rate will decrease and become zero after 2017. This is caused by the assumption of an autonomous employment growth rate of 1.75 percent. In addition, the unemployment rate is taken as the difference between labour force and employment. This means that the labour force participation rate is exogenous. In this scenario a labour shortage will arise.

In the second scenario, double dip, it takes more time to recover from the second dip in 2011. Initially the unemployment rate will increase to six percent in 2012-2013. After that, one can observe a downward sloping trend and this leads to an unemployment rate of approximately four percent in 2017. In addition, it takes more time to achieve the autonomous employment growth path of 1.75 percent. This growth path will only be achieved in 2014.

Finally, the new common scenario will exhibit an employment decrease after 2009 with the rate reaching is at its lowest level in 2011. After this year, employment will rise very slowly and will stay below the level of 2009 until 2020. The unemployment attains its highest value of seven percent in 2011. After that, a downward sloping trend commences and the unemployment rate will be approximately six percent in 2016.

In general, one can observe in all three scenarios that when the economy recovers from the negative employment growth in 2009 or from the second dip in 2011, the unemployment rate will fall. The unemployment rate in the scenarios double dip and quick recovery will fall more rapidly in comparison with the new common scenario. This is caused by the relatively lower autonomous employment growth path in the new common scenario.

There are possibilities of two demographic variations of the quick recovery scenario, namely a strong decline in the labour force and an extra migration of workers to the East. In the demographic scenario of strong decline, the labour force will decline stronger in the period 2010-2020. Via this stronger decline in the labour force, the unemployment rate will decline faster after 2010, so a labour shortage arises after 2014. Moreover, the unemployment rate will become zero earlier, namely in 2016.

Secondly, the effect of positive migration to the East. In this scenario, we assume that there is a positive migration of 40.000.000 people each year, in the period of 2010-2020. Via this positive migration, the size of the labour force will be almost the same in the period 2010-2020. The consequence of a larger labour force is that the unemployment rate will be higher and will remain high over a longer period. In 2014, it will return to its 2009 level. In the quick recovery scenario without demographic variations, the unemployment rate will return to its 2009 level in 2013. Finally, positive migration will also lead to employment growth, which will concentrate in economic centres.

In general, one can observe in the three scenarios, that a larger labour force will lead to a longer period with a higher unemployment rate. When there is a smaller labour force, the unemployment rate will be lower.

population and climate change

Climate change has been described as the biggest global health threat of the 21st century. World population is projected to reach 9.1 billion by 2050, with most of this growth in developing countries. While the principal cause of climate change is high consumption in the developed countries, its impact will be greatest on people in the developing world. Climate change and population can be linked through adaptation (reducing vulnerability to the adverse effects of climate change) and, more controversially, through mitigation (reducing the greenhouse gases that cause climate change).
The contribution of low-income, high-fertility countries to global carbon emissions has been negligible to date, but is increasing with the economic development that they need to reduce poverty. Rapid population growth endangers human development, provision of basic services and poverty eradication and weakens the capacity of poor communities to adapt to climate change. Significant mass migration is likely to occur in response to climate change and should be regarded as a legitimate response to the effects of climate change. Linking population dynamics with climate change is a sensitive issue, but family planning programmes that respect and protect human rights can bring a remarkable range of benefits. Population dynamics have not been integrated systematically into climate change science. The contribution of population growth, migration, urbanization, ageing and household composition to mitigation and adaptation programmes needs urgent investigation.

There is general agreement that human industrial activity has released vast quantities of greenhouse gases, about 900 billion tonnes of carbon dioxide, 450 of which have stayed in the atmosphere. About 80% of carbon dioxide emission is caused by industrialization and the remaining by land use such as deforestation. There is strong evidence that the burning of fossil fuels since the beginning of the industrial revolution has already caused a 0.758C rise in global temperatures and 22 cm rise in sea level during the twentieth century. During the twenty-first century, the earth’s average surface temperature rises are likely to exceed the realistic target threshold of 28C above preindustrial average temperature. The Intergovernmental Panel on Climate Change (IPCC, the leading body on climate change, comprising over 2500 international scientists) estimates that by 2100, global temperatures could rise by 1.1 – 6.48C and sea level by 28–79 cm. In addition, weather patterns will become less predictable and extreme climate events, such as storms, floods, heat waves and droughts, will occur with increasing frequency and severity.

It is important to recognize two distinct ways in which population issues can be linked to climate change: mitigation (reducing the greenhouse gases that cause climate change) and adaptation (reducing vulnerability to the adverse effects of climate change). Few experts doubt the importance of population in relation to climate change adaptation, but the link between population and climate change mitigation is more controversial. The statement that ‘people cause climate change’ is often made to emphasize that climate change, as it currently unfolds, is a human-induced, rather than a natural, phenomenon. However, the principle cause of climate change is high consumption by people in developed countries where population growth has been low or negative. At national the level, therefore, there is a lack of association between growth of greenhouse gas emissions and growth of populations during the last century. It is more accurate to say that consumers, rather than people, cause climate change; there is enormous variation in greenhouse gas emissions between individuals with high consumption levels in developed nations with low fertility rates, and individuals with low or negligible consumption in poor nations with high fertility rates. In other words, climate change is driven more by consumer behaviour than simply by population number.

Rapid population growth has a negative impact on human development, provision of basic services and poverty eradication; these effects are magnified and become more urgent in the context of climate change. Reducing the rate of population growth has long been a development goal because of the detrimental effect of rapid population growth on economic development. No country, barring a few oil-rich states has risen from poverty while still maintaining high average fertility. In developing countries, where birth rates have successfully declined ( particularly Asia and Latin America) by 25–40%, the resulting economic growth can be directly attributed to fertility decline.

In brief:
1. Rapid population growth acts in tandem with climate change to deplete key natural resources, such as water, fuel and soil fertility;

2. Rapid population growth can cause a significant increase in demand and often mismanagement of natural resources that are compromised and in decline due to environmental variability and climate change;

3. Population growth heightens human vulnerability to climate change in numerous ways and may force people to migrate to areas that are either environmentally marginal or more at risk to the negative impacts of climate change. For example, population growth in Ethiopia is resulting in soil degradation, dwindling land holdings and low agricultural productivity, which increases pressure on poor people to move either to environmentally marginal or urban areas. This leaves them more vulnerable and more likely to exploit new resources in an unsustainable way, leading to a vicious cycle of poverty and degradation

reward sharing

Reward sharing activities are well known in the business world, particularly for business relying on trust. Today, the basic concepts of Islamic economics are widely used not only in the banking sector but also in other economic sectors. In Indonesia, the concept of profit and loss sharing (PLS), contract sharing and revenue sharing can be seen as an another model to accelerate growth after cyclic downturns. There are at least three reasons why it is important to examine this concept. First, how it affects lower investment inflows, whether domestic or foreign investment. High corruption, high risk and uncertainty are the most common reasons and influencing factors for investors wanting to invest in Indonesia, although Indonesian governments have been working hard to reduce these handicaps.

Second, there are difficulties for small enterprises in getting funds from formal financial institutions and this contributes to company bankruptcies. As is commonly known, financial institutions require interest fees for credit but many small businesses cannot meet this requirement because they have not enough assets to quarantine their credit.

Third, monetary crises cause many financial institutions to have negative growth problems. However, some studies have found that financial institutions that use reward sharing in their operations were able to avoid financial crises. Some studies of the efficiency of Islamic banks have found that their practices are similar and their efficiencies are on a par with conventional banks. Other studies have found that Islamic banks are efficient in their operations. This affects the business climate; a business that uses reward sharing practices is more likely to remain operational than a business that depends for its capital on conventional banking, which relies on interest payments as its main source of revenue.

It is argued that in reward sharing system the capital owners and businessmen will work to reduce risk, in contrast with those businesses where the risk is taken by one party only, the business. As well, capital placement is not such a burden because the parties are sharing money and the financial management must be more transparent.

In addition, a reward sharing arrangement curbs, to an extent, the tendency to avarice on the part of capital owners and increases the opportunities of reward for capitalists and for entrepreneurs. Therefore, as Islam teaches us, every transaction should consider justice, fairness, transparency, and avoid ushr.

Reward sharing activities are well known in the business world, particularly for business relying on trust. Today, the basic concepts of Islamic economics are widely used not only in the banking sector but also in other economic sectors. In Indonesia, the concept of profit and loss sharing (PLS), contract sharing and revenue sharing can be seen as an another model to accelerate growth after cyclic downturns. There are at least three reasons why it is important to examine this concept. First, how it affects lower investment inflows, whether domestic or foreign investment. High corruption, high risk and uncertainty are the most common reasons and influencing factors for investors wanting to invest in Indonesia, although Indonesian governments have been working hard to reduce these handicaps.

Second, there are difficulties for small enterprises in getting funds from formal financial institutions and this contributes to company bankruptcies. As is commonly known, financial institutions require interest fees for credit but many small businesses cannot meet this requirement because they have not enough assets to quarantine their credit.

Third, monetary crises cause many financial institutions to have negative growth problems. However, some studies have found that financial institutions that use reward sharing in their operations were able to avoid financial crises. Some studies of the efficiency of Islamic banks have found that their practices are similar and their efficiencies are on a par with conventional banks. Other studies have found that Islamic banks are efficient in their operations. This affects the business climate; a business that uses reward sharing practices is more likely to remain operational than a business that depends for its capital on conventional banking, which relies on interest payments as its main source of revenue.

It is argued that in reward sharing system the capital owners and businessmen will work to reduce risk, in contrast with those businesses where the risk is taken by one party only, the business. As well, capital placement is not such a burden because the parties are sharing money and the financial management must be more transparent.

In addition, a reward sharing arrangement curbs, to an extent, the tendency to avarice on the part of capital owners and increases the opportunities of reward for capitalists and for entrepreneurs. Therefore, as Islam teaches us, every transaction should consider justice, fairness, transparency, and avoid ushr.

Gender equality and the economic potential of women

Due to large gender inequalities, the economic potential of qualified women is not optimally used. Women and men are legally equal, but clearly, they are not economically equal. Equality between women and men is one of the every country’s main objectives and tasks. However, only one in three managers is a woman, and women work predominantly in sectors or occupations where wages are the lowest. The average pay differential for men and women in full-time jobs in OECD countries is more than 18 percent. In Japan and Korea, women earn at least one-third less than men. In Germany, Switzerland, Canada, and the United States, women earn over 20 percent less than men (OECD 2008), meanwhile in Indonesia women earn only less than 6 percent than men.

In 2011 the unweighted mean for the pay gap was 23 percent in Indonesia. According to the ILO (2012) the gender inequality results in lost resources which are bad for economic growth. Or, as OECD (2008) states it, the economic potential of qualified women is not optimally used. Despite making up nearly half of the workforce and accounting for 22% respectively 24% in 2008, the Indonesian shares of female legislators, senior officials and managers among employees respectively the labour force at large were rather low, women continue to be under-represented in economic decision-making positions. Women’s untapped talent which could benefit businesses and society as a whole, represents a wasted investment in human capital (MDGs report 2011).

There are gender inequalities in labour participation, work duration, education, and wages. Moreover, there is strong sectoral gender segregation, there are few women in management functions, and few women in political functions.

Hochberg and Schmid (2005), estimate the effect of the increasing participation rate on GDP growth to be an average of 0.4 percent per annum. The effect is greater in countries experiencing strong growth, and is more limited in countries experiencing weaker growth. Löfström (2009) interprets gender labour market equality as women and men working to the same extent in paid jobs, having an equal share of part-time work and self-employment. Calculations of these gains shows that there is a potential for increased GDP of between 15 and 45 percent in Indonesia. This suggests that there are major benefits to be gained from enhancing gender equality.

With respect to women in management functions, Valerio (2009) states that women leaders are good for business. As United States businesses expand into new markets, cultures, and workforces across the United States and around the world, the companies that integrate gender diversity into their business strategy prove to be more successful. Catalyst (2004) has shown that the Fortune 500 companies with the highest percentages of women corporate officers, experiences, on average, a 35.1 percent higher return on equity and 34 percent higher total return to shareholders than did those with the lowest percentage of women corporate officers. Indonesian government should add to this that gender diversity brings a number of vital benefits to boardrooms, such as higher returns, better overall performance, better risk management and greater employment of female talents. Multiple studies show that when women are well-represented in decision-making bodies, the overall quality of governance rises and levels of corruption decrease (OECD 2008).

Gender inequality in education and a gender pay gap hamper economic growth. Remarkably, sectoral gender segregation promotes economic growth. So it is suggested that gender specialization goes along with a productivity gain. Moreover, the number of female legislators hampers economic growth and, on the other hand, the percentage of women in parliament is positively related to economic growth.

Trade Logistics Performance Index

International trade can affect jobs, consumption and poverty reduction. Logistics is a primary source of international trade costs. In developing countries, especially landlocked least developed countries, transport and logistics costs are disproportionately high, accounting for 20-60 percent of prices. A key indicator in international logistics is the dwell time – the average delay between unloading and exit – of import containers in ports. In ports with efficient freight transport, warehousing, border clearance and payment systems, to mention but a few, dwell time can be just two (2) or three (3) days. In the main ports gateways for most developing regions, it is no longer than seven (7) days or so. But in Sub-Saharan Africa, it is a staggering 14 days on average.

Supply chains – only as strong as their weakest links – are becoming more and more complex, often spanning many countries while their efficiency remains critical to national competitiveness. At the same time, logistics performance is strongly associated with the reliability of the supply chains and the predictability of service delivery available to producers and exporters.

A recent report by the World Bank – Connecting to Compete 2012: Trade Logistics in the Global Economy – makes the case that increasing logistics performance could boost trade by nearly 15 percent and benefit all firms and consumers through lower prices and better quality service. The report assesses and ranks the logistics performance of 155 countries.

 

This speech was delivered by:

Monica Alina Mustra
Trade Facilitation and Logistics Specialist, The World Bank

Education subsidies

Economic inequality touches upon the core of social and ethical thinking. Whereas economics probably is the science most suitable for making testable and measurable predictions on the causes and consequences of inequality, it is obvious that all social sciences have a place in the debate concerning the most suitable government actions of redistributing ‘the economic pie’.

If education subsidies increase (or more generally, education becomes cheaper), investing in human  apital (and thus labour quality) becomes more attractive, both for poor and rich people. However, which group will benefit the most from this is ambiguous as it may depend both on the specifications of the subsidy schemes and the ways in which individuals react to them. Perhaps even more important however, is the way in which we are actually measuring the progressivity of the subsidy. That is, before one can measure the redistributive effects of education subsidies, it should be clarified from which perspective we are measuring inequality. It is of major importance to focus on this measurement issue, since the literature is not very clear in this respect. The methods of measurement of inequality can be classified as ‘static’ (partial) or ‘dynamic’ (general).

The static perspective examines whether the direct subsidy receipts mainly end up at poor or rich households. If for example students’ access to education depends positively on household income, it may be the case that rich households deliver a relatively large amount of children at higher education institutions. As a result then, rich households would receive a more that proportional amount of the subsidy receipts. For such a measurement to be complete, it should incorporate the notion that rich households pay a higher than proportional tax amount as well. Whether they will still be better off under the subsidy will therefore depend on their net benefit. Most empirical work indeed incorporates this notion.

Whether or not subsidies are progressive, is measured by the change in household income inequality before, and directly after the subsidies are imposed. Clearly then, this measurement is conducted at a point in time and therefore can be classified as static. The dynamic perspective focuses on the general equilibrium aspect of the public subsidy schemes. That is, it is acknowledged  that subsidies are implemented to influence learning decisions of the young, thereby increasing their productivity and lifetime earnings potential. Now, to measure whether subsidies increase or decrease inequality, it is better to sit and wait for all the decisions and effects to run through the economy. Then test can be perfprmed whether or not they yield a more equal income distribution, compared to cases where no subsidy exists. Intuitively, it is unclear whether this general effect leads to a more equal income distribution. It depends on the interplay of two effects, which is known as the ‘ability effect’ and ‘wealth effect’. On the one hand, persons with a high innate ability might experience a high elasticity of education demand, because they have a high ‘return to learning’. Thus the persons, who’s earning potential is already highest, receive an extra incentive to study through the subsidy. On the other hand, this elasticity could be high for poor persons as well, to the extent that without a subsidy, they would be constrained in their decisions on education. If a subsidy is introduced, poor persons can get access to schooling and escape from the poverty trap. If the first (ability) effect dominates, education subsidies would increase inequality, while the opposite is expected if the second (wealth) effect is of greater importance. Of course the ‘wealth effect’ stands in close connection with the static effect, as they both depend on the way in which persons have access to schooling. However, the actual measurement is quite different.

So, it becomes clear that there is an enormous lacuna between the perspectives and methods of research. In the literature this gap remains open wide up and until the day of writing. Authors departing from the theoretical view have presented multiple models revealing the general equilibrium effects of subsidies on inequality. Their intergenerational models explaining the dynamic issues are highly sophisticated. In sharp contrast with the theoretical work, the empirical literature has not been able to reach beyond a measurement of the static effect.

The field of government intervention in the education sector suffers from a lack of coherent research. Whereas the authors of theoretical literature have developed a large bulk of intergenerational models, explaining the general equilibrium effects of changes in education subsidies, empirical work is restricted by lack of data. As Conlisk (1977) noted, data on matched parent-child lifetime earnings would be needed to reach to the core of the field from an empirical viewpoint. The methodology of zooming out and estimating the effects from a cross-country or macro-perspective is fragile, but might  at least offer government with a new point of view through which the general relations become clear.

The media shows a hint at a progressive effect of public education subsidies. The main channel through which the progressivity is achieved seems to be the static effect. That is, public education subsidies mainly benefit the poor because of the direct transfers they receive. Abstracting from this direct effect, the subsidies have no significant effect on inequality; it is only after incorporating transfers and taxes to our definition of inequality that the true progressive nature of the subsidies comes to the fore. All this does not imply that this paper proposes to prevent the system from changing. Recently, the notions of alternative programs of student aid, such as income contingent loans and graduate taxes are gaining ground rapidly.

Furthermore, all policy implications depend upon the preferences of the government. Most models have in common that the government searches for redistribution to a certain extent. But other aspects such as equality of opportunity and social mobility may play a role as well. So again, the mixture of positive and normative arguments appears. In that aspect, decisions on public education subsidies are no different than all other political processes; coloured by differences in ideology. The economic approach is probably most suitable to provide the guidelines of the debate. However, the theoretical and empirical methodologies attacked the problem from different viewpoints in the past. To the extent that agreement on methodology has not been reached, consensus among policy implications is even further away. Therefore, it goes without saying that this only amplifies the confusion in the area of conduct. To give useful implications for actual policy, at least need a coherent framework from which to start is needed.

Cultural Capital and Regional Labour Productivity Growth

The role of culture in economics becomes more and more important. Economic growth is long explained by Solow’s argument of capital accumulation, i.e. physical and human capital. More recently, ‘social capital’ and institutions act as additional explanatory factors (Hall and Jones, 1999). However, economists agree that there is still a large part to be further explained. That is, the so-called residual in economic growth models is still a challenge for economic researchers over the world. A recent wave of literature argues that cultural capital may be an important explanatory factor (Chartrand, (1990), Klamer (2002, 2003)). The common thought is that cultural heritage, a nice ‘green’ environment to live in, great literature, museums, theatre etc. in a region enhance the knowledge and innovative power of the working population, which lead to productivity improvements. As a result, economic growth takes place. Florida (2002) goes even further and argues that a large ‘creative class’ is the main source of regional growth.

Cultural capital is measured by local government cultural expenditures and the potential of culture measures the spatial effect.

Cultural economics is a relatively young field of research. As a result, cultural economists do not agree on fundamental questions like ‘what is culture’ and ‘what is the exact effect of culture on growth’. In addition, cultural economists find it hard to measure culture and to derive an empirical model that explains the nexus between culture and productivity growth.
However, there are some authors who have done a great effort in bundling the different views of cultural economics through time (Chartrand (1990), Dieckmann (1996), and Fukuyama (2001)). Klamer’s focuses explicitly on the theoretical value of culture and the role of culture in economics (2002, 2003). 
History of Cultural Economic Thought
Many cultural economists agree that culture is a neglected field in the history of economic thought (Boulding (1972), Meisel (1974), and Chartrand (1990)). According to Chartrand (1990) this is mainly due to Bentam (1748-1832), since he introduced the standard that culture, custom, and tradition are irrational factors that should be neglected in economic analysis. He believed in ‘radical egalitarianism’; a world where the happiness of all individuals is the same and is based on the holdings of money, i.e. the more money an individual has, the happier he is. From the mid to late-19th century, the irrelevance of culture in economic analysis was reinforced by mainstream economics, who adapted the same ideas regarding the role of culture.

Chartrand (ibid) and Fukuyama (2001) agree that institutional economists in the late 18th and early 19th century didn’t neglect the link between culture and economic growth. Chartrand (ibid, p.4) clearly describes the difference between mainstream and institutional economists in that period: “….Institutionalism is characterized by cultural, historical and legal relativism, inductive method and general systems analysis. On the other hand, mainstream economics is characterized by positivism, deductive method and mechanistic systems analysis”. The opposing views with respect to role of culture in economic thinking remained a problem in the 20th century.

Today, neoclassical economists still neglect the importance of culture, i.e. they make the simplifying assumption that human beings are rational utility-maximizing individuals. Growth is based on capital and labour accumulation. Their arguments against the use of culture in economic analysis are intuitive. That is, they argue that cultural factors are, methodologically, very difficult to measure and that empirical evidence is weak. However, a counterargument against their theory is that they fail to explain the so-called ‘Solow residual’, i.e. it has been shown that it is impossible to explain economic growth by economic factors only (Dieckmann, 1996).

In the mid-eighties of the 20th century, endogenous growth theory has been introduced (Barro and Sala-i-Martin, 1995). As Dieckmann (1996) argues, endogenous growth models are based on imperfect competition and they explicitly include human capital accumulation, R&D expenditures and other determinants that are related to culture. Hence, in this new way of economic thinking, culture is more and more treated as an additional explanatory factor. Moreover, new institutional economists in the late 20th century showed their renewed interest in culture. According to Fukuyama (2001) institutional economists nowadays seek to give rational, maximizing accounts of the origins of institutions, but as a group they are much more aware of the importance of history, culture, tradition, and other so-called ‘path dependent’ factors in shaping economic behaviour.

In short, being invisible for centuries, cultural economics finally receives some attention in modern economic thinking. However, a lot remains to be explained; what is culture exactly, how can we assess culture, what is the evidence regarding the relation between culture and productivity growth, and how can we explain the relation?
The Value of Culture
According to Klamer (ibid), cultural value can be analyzed by four different lines of inquiry. In the first interpretation, ‘value’ refers to ‘economic value’ and ‘culture’ to ‘high culture’. Topics that fall under this interpretation are, for example, the economics of cultural heritage and the economic impact of government subsidies on cultural goods. Second, value can also refer to value in a social and cultural sense. A monument or museum often generates national pride and cultural identity. Social values play a role in arguments that favour the subsidization of cultural goods, since they improve the integration of minorities, have educational values, and are good for personal development (Klamer, 2003). A third interpretation is that culture has anthropological meaning. That is, culture leads to the shared values, stories and aspirations that distinguish one group of people from another (a community, an organization, a region). The economic value of culture then implies the economic contribution of these shared values. This interpretation is analogous to Weber’s work (1930). He argued that a particular culture may improve economic performance or hinder it. The final interpretation combines all previous interpretations. That is, culture may stand for both the arts and culture in the anthropological sense, and value for economic value as well as social and cultural values.

Klamer (2003) explains the link between the four interpretations as follows: “Whereas the common justification of cultural policy evokes the economic value of culture (think of the income generated, the increase in tourism and the attraction for new businesses in town) or social values (educations, inclusion of minorities, low thresholds for people with a low income), culture can also be said to have value in and of itself. It could even be argued that all economic activity serves the enhancement of cultural ‘capital’ of a community, such as a town, or a country” (Klamer (2003), Ch. 59).

According to Chartrand (1990), cultural economics can be defined as the study of the evolutionary influence of cultural differences on economic thought and behaviour. That is, economic behaviour varies because of a changing cultural context. The economics of culture, on the other hand, can be defined as the study of the allocation of scarce resources within the cultural sector. Objective laws apply to economic behaviour regardless of cultural differences, i.e. a positivist approach. My study is a cultural economics study since I focus on the influence of cultural differences on economic performance, i.e. labour productivity growth.
Assessing Culture
Klamer doesn’t explain how we can make his ideas operational, i.e. assessing different cultures. Fortunately, Hofstede’s (1978) work does explain how to assess culture. His framework for assessing culture in a society (country, region, or organization) consists of four dimensions. The first is power distance. It relates to the degree of inequality in power between people in a particular society. Power is the potential to determine the behaviour of other persons. The higher the power distance, the more inequality in power between people, i.e. the more hierarchy in decision making. The second is individualism. This dimension focuses on the degree to which a society reinforces individual or collective achievement and interpersonal relationships.

Individuality and individual rights are important for cultures based on individualism and the ties between individuals, i.e. family relationships are important for cultures based on collectivism. Masculinity is the third dimension. It refers to the inequality between genders in a society. It relates to the degree of a society to reinforce or not the traditional masculine culture of assertiveness, ambition, and the accumulation of wealth and material possessions. Relationships and the quality of social life correspond to a low degree of masculinity. The fourth is uncertainty avoidance. This dimension concerns the level of acceptance for uncertainty within a society. Cultures that score high in uncertainty avoidance prefer a rule-orientated society that follows well defined and established laws, regulations and controls.

Culture and Productivity Growth
Again, cultural economists do not agree on the exact relation between the two. Due to measurement
problems and data limitations, empirical evidence scarce. As a result, cultural economists mainly focus on a theoretical foundation.
One of these authors is Chartrand (1990). He argues that culture influences productivity growth via technological change. Technological change is widely accepted as being an important factor influencing growth. In general, technological change is achieved by creating new ideas, innovations, inventive organization structures, and developments in advertising techniques. Chartrand (ibid) argues that cultural capital leads to technological change, since cultural experience of the labour force leads to the creation of new ideas and innovations. This theory seems rather unconvincing at first sight, but it comes close to reality. Look for example at the multinationals nowadays; they are looking for new, creative employees constantly. That is, workers who have a personality, who are diverse, and who have refreshing and new ideas. Hence, Chartrand’s work deserves attention.
Unfortunately, his theory is not based on any empirical evidence, which makes it rather subjective. He only shows the positive relation between rapid urbanization, technological change and a higher level of education on the one hand, and an increase of expenditure on cultural consumption goods on the other. Nonetheless, he stresses the importance of data requirements; he shows that there are a lot of opportunities when more cultural data becomes available.

Fukuyama (2001) also provides a theoretical explanation for the nexus between culture and productivity growth. He notes that cultural factors affect economic behaviour generally in four ways. The first is the impact of culture on organization and production. Firms around the globe have different hierarchical structures, norms, production processes etcetera (Hofstede, 1978). Some ‘organization cultures’ do better than others and make more profit. The second is the role of culture in consumption behaviour and work ethic. Different classes of societies, like rich and poor, have different cultural habits and different consumption patterns. Income and cultural expenditures are thought to correlate positively. The third is the ability of culture to create and manage institutions. Many economists agree that institutions are important determinants of the economic performance of countries. Culture in its broad sense affects the ability of societies to create and manage institutions. The fourth is the impact of culture on social networks. The impact cultural values have on networks of social relations is the basis of social capital. Social capital consists of norms and values shared among a group of people that promote cooperation and confidence among them. Hence, it refers to the flow of information in an economy. Information indeed becomes more and more important in today’s world, notice the current credit crisis. A lot of miscommunication and imperfect information lies at the basis of the crisis. Nevertheless, the concept of social capital has been criticized for being a rather vague concept and the lack of a clear measurement method.
The analyses of Chartrand and Fukuyama have one thing in common: culture affects productivity growth indirectly. It implicates that the effect of cultural capital on growth is difficult to disentangle from other factors of influence, like institutions and social networks.

Off shoring effect

Offshoring and outsourcing have been studied by many economists (see for example Antras et al (2005), Grossman and Rossi-Hansberg (2006) and Deardorff (2005), among others). In (economic) geography however, there hasn’t been done much research about offshoring and outsourcing yet. Although in the field of firm demography, which can be thought of as a segment of economic geography, many studies have been published about the birth, death and migration of firms, this is mainly focused on the firms within a country. An important reason for this is of course that firm migrations abroad account only for a small part of all the firm relocations. Furthermore, firm demography is mostly concerned with the relocation of complete firms, not the relocation of certain activities, as is the case with offshoring. However, the number of firms moving activities abroad is increasing. It also shows that the yearly percentage of firms that relocated activities has increased over the studied period. All changes in the locations of companies and corresponding changes in the places of production and services activities have an impact on the economy in Indonesia.

Although scientific research shows that offshoring and outsourcing have been steadily increasing, it is still low. However, the recent media and political attention on production and service offshoring from developed to developing countries gives the impression that outsourcing and offshoring are exploding. As a result, workers in industrial countries are anxious about job losses (Amiti and Wei, 2004).

One of the first questions that comes up when studying these relocations is; what is exactly the difference between outsourcing and offshoring? So far, these two concepts have been used interchangeable. However, there is a difference. Outsourcing and offshoring are related to the ‘make or buy’ decision. A firm can decide to subcontract part of the production capacity or services to another company, which is called outsourcing. If a firms decides to relocate part of their activities abroad, this is called offshoring. Offshore outsourcing is subcontracting a part of the activities of a firm to a foreign country. Offshoring without outsourcing means that the firm will take over an existing firm or set up a new firm abroad (Poort et al., 2004 and Ministry of Economic Affairs, 2005). 

Outsourcing and offshoring can be seen as part of international trade. Instead of producing a product in a developed country, it is now imported from developing countries where labor is cheap and abundant. However, the renewed attention for offshoring is caused by the fact that the relocation of production is no longer confined to the situation where only low skilled production was transferred to low wage and labour abundant countries, as would be expected by examining the neoclassical trade theories. Increasingly, high skilled jobs, (for example ITservices) previously thought to be safe from competition from low wage countries are also shipped abroad.

A requirement that foreign companies sell 51 percent of their mines to Indonesians within 10 years of production is hurting exports such as nickel and copper ores. But at least in the latest quarter, new investment has started as miners seek to comply with new rules that they build local smelters or process ore domestically by 2014. 

In contrast to this pessimistic view, outsourcing and offshoring can contribute to the maintenance and development of employment in the developing countries. Because of savings, improvement of the competitive position and perspectives for new investments, new high skilled jobs can be created. According to Deloitte (2006), the process of offshoring in Indonesia is already on its return. Most profit is to be gained in the optimization of the production process and the improvement in the chain management (Deloitte, 2006). This means that the separate locations will have to be integrated into one production network with planning on a broader scale. Relocations consequently only make sense if it happens in combination with a thorough thought and centrally led production chain.

That offshoring and outsourcing are still very low can also be shown from the fact that in many industrial countries ‘insourcing’ is greater than outsourcing (Amiti and Wei, 2004). Insourcing can be described as the opposite of outsourcing and offshoring (investments from foreign located firms to domestic firms). Amiti and Wei (2004) used the exports of business and computing services from the IMF Balance of Payment Statistics Yearbook 2002 as a proxy for insourcing. 

However, scaling the export value by the size of the GDP, smaller economies tend to be more insource-intensive than the larger ones. The top three now consists of Vanuatu, Singapore and Hong Kong (Amiti and Wei, 2004). It is arguable whether business and computing services is a good proxy to measure insourcing. Although studying the effects of outsourcing and offshoring on recipient countries goes beyond the scope of this thesis, it is an important aspect of firm relocations. According to Folmer (Volkskrant 13 april 2004), offshoring and outsourcing are new ways of  development aid because developing countries become an interesting firm location. Furthermore, there is a shortage of labor in developed countries in sectors like the IT and care, and personnel in developing countries can help to reduce the scarcity. As a result, migration from developing to developed countries will decline.

Defining outsourcing and offshoring
First of all, the distinction between outsourcing and offshoring has to be clarified. This distinction is not clear-cut and the two concept are often used interchangeable. According to Biermans and Leeuwen (2006), the meaning of the term outsourcing has changed the last couple of years, but the original definition is still in use:
Outsourcing describes the act of obtaining services and/ or goods from an external firm (Biermans and Leeuwen, 2006).
The definition of offshoring most frequently used in the literature is very broad. Biermans and Leeuwen (2006) describe it as ‘the relocation of production abroad’ (p. 9). Ter Beek et al. (2005) defines it as ‘the relocation of labor to low income countries’ (p.4). The definitions of Poort et al. (2004) and Berenschot (2004) are similar: ‘offshoring is the relocation of activities to low income counties’.
The most important aspects of offshoring are:
– relocation
– activities
– low income countries
Outsourcing can be seen as a part of the offshoring process, however, outsourcing does not have to include offshoring and it is also possible to offshore without outsourcing. This can be clarified by making the distinction between the location of the activities (national or abroad; onshore or offshore) and the type of ownership (the make or buy decision; in-house or outsourcing).

However, there are some more considerations concerning offshore outsourcing and foreign direct investments that have be kept in mind.

1. These foregoing definitions do not take into account the distance to place of the relocation. 
2. Another consideration is the type of activities that will be moved abroad: production
(e.g. the production of electronics in China) or services (e.g. the call centers in India). Offshoring services, in particular IT-services, can be done in three ways: captive service provisioning, native service provisioning and foreign service provisioning (Beulen, 2005). Captive (or in-house) service provisioning means setting up an own service center in a low income country. The firms has to make considerable investments (FDI) in this country. In the case of native service provisioning, a company outsources the work to a local IT-supplier, and this local IT supplier gets the work done offshore. In the case of foreign service provisioning, the company outsources the work directly to an offshore IT-supplier. Both native service provisioning and foreign service provisioning come under the heading of offshore outsourcing. A familiar example is an IT-company in India that develops software for
a company in Indonesia. If this Indonesian company is a non IT-company, it is called foreign service provisioning, and if in case of an IT-company, it is called native service provisioning.

Low skilled service and production jobs where personal contact is necessary won’t be offshored, which means that demand for hairdressers, cleaners and plumbers in developing countries will continue to exist.

One relatively recent aspect of service offshoring is that people in developing countries go to developed countries for a medical operation or cosmetic surgery. This market has especially been booming in countries like Turkey, Thailand and Brazil. This is also a part of the offshoring process, as it does fit into the broad definition of offshoring as an relocation of labor to low income countries. One of the reasons of this is of course the differences in prices for these operations.

3. Third, an essential question is which markets are being served by this new location. A distinction can be made between horizontal FDI and vertical FDI. Horizontal FDI serves foreign markets, new markets will be opened up to sell the products. This has not necessarily negative effects on employment in the home country. Vertical FDI combines serving the home country and opening up new markets with the (partly) replacement of production or services in the home country. The effects of an expansion of vertical FDI on the home country are ambiguous (Biermans and Leeuwen, 2006).

4. As said before, offshoring does not necessarily lead to (total) outsourcing. It is possible to open an own company or set up operations with other firms. Deloitte, cited in Ter Beek et al. (2005), distinguishes five ways to offshore activities:
– outsourcing: total subcontracting to a third party
– joint venture: setting up a new operation together with a third party
– wholly owned: set up a new firm as a subsidiary company
– turnkey: asking for the help of thirds, but keeping the full control over the operation
– indirect: collaboration with a third party who uses offshoring

Public policy and offshoring
In deciding what policy to use to influence the decisions of companies whether or not to relocate a low cost country, two points are important:
1. Keeping existing firms in the region. However, this doesn’t means that the work needs to remain the same.
2. Attracting new firms to the region. Attention will be paid here to the different ways that regional policy in Indonesia is able to influence the companies within the country. Embeddedness, innovation and education play important roles in formulating these policies. Both the new economic geography and the institutional theory provide a theoretical framework for this.

In general, public policy concerning offshoring should target the improvement of the competitiveness and entrepreneurial climate in Indonesia. Policies that prevent offshoring (and the loss of employment) might backfire because the choice facing some industries is to offshore or cease to exist (Robert-Nicoud, 2006). This means that eventually these companies will leave the region even when measures are implemented that will prevent the company from leaving the region. Some of the measures include giving companies a tax advantage when keeping employment in the country or region, introducing a tax when companies want to relocate labour and letting an independent organization test the offshoring plans of companies (Poort et al., 2004). Furthermore, these tax measures will probably cause companies to go for offshore outsourcing, in which formally no labor is being relocated, because of ownership changes. These measures might not be the optimal choice for a company, reducing the competitiveness of the company.

Improving the position of Indonesia by keeping existing firms in the region and attracting new firms can be done in different ways, that reinforce each other when implemented the appropriate way. Points of attention include embeddedness, innovation and education. These aspects are also important in the report of the Ministry of Economic Affairs.

Recommendations:
– The government needs to address the shortage of skilled talent, especially for technical professions. Investments in science and technical educations need to increase to ensure continued global competitiveness. 
– Increase the education of the labor force, making sure that the labor force meets the demand of the companies in the North. The labor force needs to be used up to its maximum. This means promoting and investing in higher technical education.
– Create embeddedness; strong social relationships and strong networks between companies in the country.
– Use city and region marketing as a tool for making the region more attractive for (innovative) companies to locate. Create an innovative environment for these companies. Infrastructure, living and housing conditions, educational opportunities and the supply of business areas need to meet the demands of the companies and its employees.
– Improve the innovativeness of the existing and new firms in the whole regions by creating strong relationships with the Universities (innovation campus) and other higher education in each region.
– Set up retraining programs for (older) employees that are laid off. They have often worked for one company a lot of years and it is hard to find a new job in the same sector.

Economically active population

The land of Thousands of Island is known for its unique culture and majestic beauty. The cultural fervor of the country is reflected in its population which counts to around 201 million people. The Indonesia population makes it ranked fourth in the world only after China, India and United States of America. Out of the more than 13,000 islands of the land only a handful are inhabited that shoots up the population density of the country to a higher level. The island of Java upholds it with more than 107 million people living in that island in an area which spreads to not more than the area of New York State. The Indonesian population presents the picture of a mixed group of ethnic cultures and several linguistic groups.

 

The increase in population size has been the result of fertility and mortality trends, while international migration has not played a determining role in Indonesia (Dobossy et al., 2003). The combination of these fertility and mortality processes is also called the demographic transition (Hilderink, 2000). 

Fertility is measured by the Total Fertility Rate (TFR), which is defined as “the average number of children that would be born per woman if all women lived to the end of their childbearing years and bore children according to a given fertility rate at each age (CIA World Factbook, 2012).‟ This is a period rate, which is widely used and measured among demographers. From this point forward, all TFR references are referring to the period total fertility rate, unless stated otherwise.

The fertility rate in Indonesia is now down to about 2.1 which is almost exactly replacement level and suggests that population will stabilize in the foreseeable distant future. Women are also having babies later, which also slows the rate of population growth. The UN’s medium population projection is that fertility will continue to fall to around 1.85, which would mean the total population, now 232 million, would stabilize at 290 million soon after 2050. However, if fertility falls faster than expected, population could peak by 2035 at just 257 million. As is it, the population is now only growing at barely 1 percent compared with over 2 percent in the 1970s and 1980s, and the rate of increase will continue to fall year by year. The country is also now in the very usual position that the total number of people in each five-year cohort between 0 and 30 is almost exactly the same size: 20 million. There is no baby bulge or bust to worry about.

There are several positive consequences of these overall trends. The first is that the percentage of the population in the 15-59 bracket has already reached 64 percent compared with 58 percent in 1990. This will edge slightly higher to 65 percent by 2020 but essentially is now on a plateau and will remain there for a long time. The median age, which in 1990 was only 21, is now 28 and will climb to 32 by 2020. In other words, it is entering the range which, other things being equal, individual enterprise and productivity are at their peak. 

The second is that the pressure for new job creation is easing rapidly, making it more likely that the nation can focus more on quality and productivity. The working-age population grew by 26 million between 1990 and 2000, but the increase fell to 23 million in the decade just ended and will be only 20 million in the decade to 2020. Meanwhile, it will be another two decades at least before the percentage of old people becomes a significant issues. The 65-plus group will be only 7.5 percent by 2020 compared with 6.1 percent today. 

Another benefit, at least compared with sexist neo-Confucian countries and parts of India, is that there is no male preference. The ratio of male to female births has been steady at a natural 1.05 for decades. This in turn makes it more likely that fertility will stabilize at or near replacement level while China’s shortage of women will undermine its efforts to sustain the birth rate. Raising the fertility rate (births per woman) to a replacement level of 2.1 will be of limited value if there is a 15 percent shortfall in the number of women (as is the case now in the 0-10 group). 

The mortality trends in Indonesia have also shown a diverging path from the average South East Asian mortality development. Indonesia has been characterized by a high mortality level relative to the social, economic and cultural level of the country (Kamarás, 1999). The increasing mortality affected the working age males and females (Valkonen, 1991), whereby the increasing mortality of middle-aged (30-59 years old) males was responsible for 85% of the mortality increase. Jozan (1991) relates the unhealthy lifestyle and Valkonen (1991) relates the increased amount of cardiovascular diseases to be the cause of male health deterioration.

Directly related to the mortality is the life expectancy at birth, which also suffered from the above mentioned. A widening gap between male and female life expectancy arose between 1980 and 1996, resulting in a male life expectancy at birth of 69,8 and 77,8 years for females in 2008. Although male and female life expectancies at birth have witnessed growth over the past 20 years, they are still lagging behind the South East Asian average (WHO, 2010).

The population decrease occurred simultaneously with the ageing of the population. This is shown by an increasing number of the population aged 65+ and a decrease in the number of under 15 year olds, thereby changing the ratio of elderly persons to that of children (the ageing index) in the advantage of the elderly. The growing amount of elderly people has its impact on the dependency ratio (number of people aged 0-14 and 65+ divided by the number of people aged 15-64) and the old age dependency ratio (number of people aged 65+ divided by the number of people aged 15-64). This leads to an increased burden on the active labour force, which is paying the taxes that make the system of Indonesian social securities, pensions and retirements, work.

The development of the labour force therefore plays a crucial role in the maintenance of the public finances (Euwals et al., 2006). Measures to re-establish a stable supply of labour have to be taken, as ageing puts pressure on the (supply of) labour force and therefore on the public finances. The two most effective measures to increase the labour supply are an increase of the labour force participation and a reform of the social security and retirement agreements (Euwals et al., 2006).

It is expected that an increased flexibility and higher employment rates will result in increased labour participation rates for males and females, which is a necessity to overcome the increasing costs of an ageing society.

Multidimensional poverty risk of vulnerable households in Indonesia

Since transition, there has been divergence between economic and human development in each region in Indonesia, which gives rise to question whether the use of a multidimensional approach instead of a financial assessment of poverty leads to a different identification of vulnerable socio-demographic groups. Moreover, every province of Indonesia is very diverse, which suggests that the relation between socio-demographic household characteristics might vary between different regions in the country.

Ellis (2000) developed a theory which is based on the capabilities approach as developed by Sen in 1983. This approach to assess human well-being evolved from the basic needs approach, and rejects the use of an objective financial cut-off for poverty, and a focus on only physical assets and the utility gained by individuals. The focus of the capability approach is on the ability to act and views commodities as means, not as ends to achieve a certain standard of well-being. The livelihood framework distinguishes assets, access, and activities, which together determine the living gained by an individual or household. Another alternative approach to measure well-being is by using subjective well-being or life satisfaction, which originates on the work of Easterlin (1974) who linked psychology to economics. Subjective well-being is also viewed as an household asset, and is with other (more objective) indicators of household capabilities integrated in a multidimensional well-being index.

The construction of the multicomponent index is based on earlier work of Klasen (2000) and Guio (2005). Research of the World Bank (2000, 2005) showed that well-being problems in Indonesia are mainly linked to housing and (semi-)public services, such as health care, education, and utilities. Moreover, studies by a.o. Bezemer (2006) and the World Bank (2005) show that women, children, elderly, and households in rural areas are vulnerable groups in Indonesia. Other research by the World Bank (2006) adds that there is a concentration of deprivation in secondary cities. Moreover, vulnerable households tend to be trapped in bad general living conditions with restricted access to improvements in their well-being situation. Further, some sociological case studies by Smith et al. (2006, 2008) and Stenning et al. (2007) show that low welfare is strongly connected with low skill, bad health, unemployment, and old age in poor areas. Moreover, Smith (2000, 2003) finds that regional welfare is strongly connected with industrial activity and high skill levels.

Financial poverty is defined as an inadequate level of income to satisfy basic material needs. Multidimensional poverty (or deprivation) is defined as an insufficient level of capabilities to meet basic needs. For both poverty and deprivation, a 40% and 20% cut-off point is used to compare the vulnerability of households based on both measurements of well-being. 

Kompas stated that for many households financial poverty and deprivation do not overlap necessarily. With a lower poverty line, the overlap between the two different poverty types is even smaller (relatively). The relation between poverty and deprivation ranks of households is also quite weak. This is in particular the case for the worst-off households in Indonesia.
Besides the obvious differences in poverty and deprivation rates between the regions, the differences between the poverty rate and the deprivation rate in each region is surprising. The ‘richer’ regions have a relatively high deprivation rate, while the poorest regions experience a deprivation rate that is low in relation to their financial poverty rate. 

Social inequality and public health

The negative effects of inequality became a hot topic among epidemiologists and other social scientists after the landmark book ‘Unhealthy societies: the afflictions of inequality’ by Wilkinson in 1996 arguing that unequal societies are simply unhealthier for their members. Since then socio economic inequality has been blamed with bringing many miseries: shorter life expectancy, higher rates of disease, homicide, infant mortality, obesity, teenage pregnancies, emotional depression and crime, poor education standards, lower social mobility (Wilkinson, Pickett, 2009), higher prevalence of smoking and sedentary lifestyle (Diez-Roux et al, 2000, cited by Kawachi et al, 2003), less trust within the society (Elgar, 2010) and lower social capital (Kawachi et al, 1997, cited by Salverda et al, 2009).

Social inequality has been growing steadily in all modern societies since 1970s (Beck, 2007; Beck & Poferl, 2010; Grusky & Kanbur, 2006; Korzeniewicz & Moran, 1997; Morris & Western, 1999, cited by Castillo, 2011, Subramanian and Kawachi 2004, cited by Torre & Myrskylä, 2011). It has been increasing rapidly in such important cases as China, the U.S.A. or the former Soviet bloc (Babones, 2009).

However, while those more deprived were willing to tolerate the differences during the economically good times it is now changing. During the recent economic recession the contrasts between the upper social class and the lower social class appear to be unacceptable to many (Dorling, 2012).

The recent developments show how inequality is becoming more of an issue: the social inequality is addressed often as an important problem by politicians and media (Miller, 2012). Social inequality does undermine the social cohesion and trust most of the questions about the deleterious effects (among them those on the public health) of inequality still remains open and very controversial. Since 1996 the association between inequality and public health has generated a vast body of research with no definite general conclusions. Since then it has remained highly ideological it has received a lot of attention not only from academia but also from the general public.

Various public health indicators were previously related to social inequality, most usually life expectancy, mortality or their derivatives (for instance, a dispersion measure that equals the average expected lifetime lost at death (Shkolnikov et al, 2011)) but also disease rates, disabilities, smoking, sedentary lifestyle, depressive symptoms, per capita expenditures on protection and medical care, self-rated health (Kawachi et al, 2003). All of them have their drawbacks. Life expectancy, mortality or self- rated health seem to be the most comprehensive but it has been argued that self- rating of health is far from objective. For example, people in Jakarta, the most upper social state in Indonesia reported having poorer health levels than in more deprived state of Bandung which could refer both to subjectivity of health rating and to confusion between mortality and morbidity (Sen, 1999, cited by De Maio, 2008). Self- rating is problematic for the reason that poorer people tend not even to be aware of some disorders they have, e.g. hypertension (Johnston et al 2007, cited by Salverda et al, p.393).

Life expectancy or mortality numbers however do not say much about the health of the living (Salverda et al, 2009, p. 393). A time lag has been often used to account for this assuming that the harm to the public health is reflected in the mortality numbers after a certain number of years. There exists, of course, a big variation in the duration of the lag making it impossible to pinpoint when the effects of inequality manifest (Zheng (2012) argues that the effects of inequality are the strongest after 7 years but remain significant up to after 12 years) and primarily depends on the nature of the disease. It can be argued however that the mortality developments are usually smooth and gradual and strongly correlated to those of earlier years (further here the time lag is not used to enable easier comparability between all- cause mortality and external- cause mortality where the effects are assumed to be contemporaneous).

More recently the specific reason of death have been started to be researched more deeply offering more precision in unmasking the pathways in which the inequality manifests. This is done for a number of reasons. Firstly, if the mortality is dominated by one or a few main causes (e.g. hart and coronary diseases, a common dominant cause of death) the existing effects on other causes of mortality might be left unobserved. Secondly, different causes of death respond differently to inequality. Some might be more sensitive than the others, (e.g. in the common practise it is known that for example alcohol while being a risk factor for some diseases can also alleviate others), and therefore analyzing all- cause mortality only masks the true effects of inequality (Spijker & van Wissen, 2010).

Thus besides all- cause mortality also external- cause mortality is used further in this research. The external causes of death include (according to WHO mortality database ICD10) death from transport accidents, falls, accidental drowning and submersion, exposure to smoke, fire and flames, accidental poisoning by and exposure to noxious substances, intentional self-harm, assault and other.

Analysing external cause mortality with regard to inequality is extremely relevant as it seems to be very sensitive to the socio- economic and political changes (Peck et al, 2007). As the name itself indicates, the reason of death lies by definition outside the person affected. The social instability seems to correlate with the deaths rates due to injury, an example of this is the fluctuations in mortality immediately prior and after the reformation era. Another example is change in mortality in the post- new orde after the transition to the reformation era.

The age- standardized mortality increased 33% for men in Indonesia 1999-2010 and mortality from injuries constituted one third of the decrease in life expectancy (Peck et al, 2007). As mentioned previously, psychosocial factors are assumed to play an important role regarding the external- cause mortality as the external causes of death are often associated with aggression, violent behaviour, inadequate risk taking, drugs/ excessive alcohol consumption or negligence: factors that are more of psychosocial than biomedical (as for most of the other causes of death) nature.

The effects of inequality and mortality are examined separately for genders, age groups and causes of death. The differences in mortality between men and women are well known which applies for both external and internal reasons mortality (Krugger & Nesse, 2006). As long as no artificial barriers for women are created (e.g. infanticide, neglecting the female children) women tend to live longer, especially in developed countries where the risk of dying due to reasons related to maternity are low (Omran, 2005).

The differences in mortality are partly explained by the theory of sexual selection. Males (especially the young males) compete for the females, often engaging in violent and risky behaviours creating real threats for their lives. (Krugger & Nesse, 2006) The competition (and the mortality) gets harsher if the stakes are higher, e.g. under the circumstances of polygyny ((Plavcan, 2000; Plavcan and van Schaik 1997; Plavcan, van Schaik,and Kappeler 1995, all cited by Krugger & Nesse, 2006) an analogy to which of course in this case would be high inequality.

Even in the modern humans’ societies high social status increases the chances to find a mate more for men than for women. Besides in the societies with the man as the bread winner model men feel more responsibility to maintain or improve the socioeconomic status of the family (Torre & Myrskylä, 2011) and thus are more subject to the adverse effects of inequality.

Examining the effects of inequality on external- cause mortality gender is extremely important. Besides the theoretical reasons the empirical external- cause mortality data also shows an age- sex pattern distinct from that of other causes (Jakubonienė et al, 2010) which cannot be explained in terms of the development level of the region and is likely to be determined by the societal environment.

In previous studies that have discovered correlation between income inequality and health outcomes there were different opinions on if the relationship is causal (Babones, 2008, Mellor & Milyo, 2001, de Maio, 2012). It has been often argued that both inequality and public health depend on the same underlying factors (Salverda, et al, 2009, p.385, Babones, 2008). Cultural and historical factors determine the distribution of the income in a country. The income distribution systems grown organically from the environment and it would be too easy to think that Indonesia would be just like Malaysia was only the income distribution changed (Saunders, 2010).

There has been a variety of the underlying factors determining both the inequality and the public health suggested: level of trust in the society as the level of trust in the society in negatively associated with inequality and positively associated with better public health (Elgar, 2010); IQ: more intelligent societies both create more egalitarian societies and are healthier (Kanazawa, 2006). The latter was severely criticised, for instance Marks described Kanazawa’s data as ‘allegedly supporting a racist version of evolutionary psychology’ (2007). According to Mellor & Milyo, inequality in different contexts can be related with both better and worse population health.

In the light of the psychosocial interpretation it can be assumed that the underlying factors can be the traits and predispositions of the society that determine how it accepts and deals with the economic inequality. The social justice ideas the society holds, the power distance and masculinity dimensions in its culture (as described by Hofstede, 1980), the political and economic regime (e.g. a socialistic versus aristocratic or plutocratic) can determine what perceptions and psychosocial reactions are then formed in response to a given inequality (Paškov, 2008).