Will higher income improve nutrition?

Yes, according to a conventional wisdom in development economics in the '70s-80s. This was based on several findings that higher income leads to higher food consumption. One estimate (now have to find out where did I read that) on income elasticities of food expenditure was 0.8. It means that economic growth or any process that leads to higher income is good: it also leads to improved nutrition.

One major problem with this view is that increased food consumption may not lead to better nutrition intake. When their income increases, poor people may opt for a different type of diet (better taste or more variety of food) but not necessarily better nutrition. So we need to look more on the direct relations between income and nutrition. Behrman and Deolalikar 1987 found that in rural Maharashtra, India, indirect measurement of elasticity was 0.77, but the direct measure was only 0.17.

Then, there are some issues concerning choice of empirical method. Here I will particularly look at one type of nutrient, calorie. But the issue holds for nutrient in general.

Income or expenditure?

A classical issue. Ideally we would use income as it is our variable of interests. But there are many problems in collecting income data. Moreover, current income is more volatile hence a more noisy proxy for permanent income. So, in many cases, we need to rely on expenditure. In general, measured elasticity is lower when we use income.

Calorie intake or availability?

A more accurate measurement is individual calorie intake. But that will require an intensive data collection. We need specially trained diet investigators to measure individual dietary intake in their houses for a specific time. Not that it is impossible - for example they did this in India (see Behrman and Deolalikar 1987) or Bangladesh (see Pitt, Rosenzweig, Hassan 1990).

In other cases, we need to rely on the calorie availability. That is, the information on the amount of specific types of food they purchased over a specific time, and convert them to calorie intake. The main problem with this approach are wastages and leakages. What is available may not equal to what is consumed. People just don't eat up all their available food, or household might have shared or served some of their food to guests or non-household member. Another problem is more often we can only have the data in the household, not individual, level.

Another issue is estimating elasticity at a single point, for example at mean or median, will not give an accurate picture of the variations across people from different income groups. A mean or median estimation may understate the income elasticity of calorie of the poor people. A better approach is to do separate estimation for different income groups. Non- or semi-parametric approach may also work, like Gibson and Rozelle (2002) did for urban Papua New Guinea. They found he income elasticity of calorie was 0.6 for the poor, but declined rapidly for once calorie intake reached 2100 cal/day.

The bottom line: higher income may not always prevent undernutrition. We need to look more into individuals and households make decisions, including intra-household allocation of resources. Among other things, women's education could be one significant aspect in improving household demand for, and quality of, nutrition, argued Behrmand and Wolfe (1982).

Market failure and health care needs

Philip Musgrove (2004:54-55, based on his earlier 1995 article)* explained why, in the health care market, demand does not equal supply, while at the same time demand and supply may not equal to the 'need' for health care.

Demand does not equal need

Budget constraints, due to either poverty or the high cost of health care are two obvious reasons why people demand health care less than what they actually need. Lack of information. Lack of information may contribute as well, for example on what type of health service they can or should attain for a given illness. On the other hand, in many cases supplier induced demand made people consume more health services and product more than what they need. Finally, externality and public goods nature of health service made people demand too much or too few.

Supply does not equal need

Because demand is often not a true reflection of need, then there is no clear signal for supplier about the true consumer's need. But in many cases, market incentives may induce supplier to supply regardless of the need. On the other hand, for some types of services, the cost is too prohibitive for supplier to deliver health care of services, so they end up supplying less than what is needed.

Supply does not equal demand

This is a classical case of market failure, due to asymmetric information and other barriers to competition. But non-market incentives, such as political or cultural issues may also be the reason.

*Musgrove, Philip (2004), Health Economics in Development, Washington, D.C: World Bank.

Constructing risk preference

The next step to my Possible Topic#2 (although the preliminary result was not too encouraging) is to construct individual risk preference coefficients.

A respondent was asked this question:

You have an equal chance of receiving either Rp1.6 million per month or Rp400 thousand per month, depending on how lucky you are. Option 1 guarantees you an income of Rp800 thousand per month. Which option will you choose?

If he chooses (2), the riskier option, then we assume that he prefers (2) to (1). That means U(2) > U(1).

We assume a constant relative risk aversion (CRRA) utility function (following Binswanger 1980, Holt and Laury 2002, Kimball, Sahm and Shaphiro 2009, Cameron and Shah 2009, and many more):

W^(1-r)/ 1-r

where r is the Arrow-Pratt coefficient of relative risk aversion defined as:

- WU''(C) / U'(C)

Hence, for the above gamble, we can write the individual's preference as:

0.5(1600^(1-r)/ 1-r) + 0.5(400^(1-r)/ 1-r) - (800^(1-r)/ 1-r) > 0

Solving the inequality, we get r < 1.

Now, let's say the individual chose the safer option for the follow-up question:

You have an equal chance of receiving either Rp1.6 million per month or Rp200 thousand per month, depending on how lucky you are. Option 1 guarantees you an income of Rp800 thousand per month. Which option will you choose?

The solution is r > 0.3058. So, for this individual, we conclude that his risk aversion lies between 0.3058 and 1, or 0.3058 < r < 1. Higher r implies a greater risk aversion, while lower or negative value of r implies a more risk-loving behavior.

Not-so-encouraging results

A first shot to see if my Possible Topic#2 might work. The results, unfortunately, are not so encouraging.

Here's why. The first of the hypothetical risk question is a filter to sort out ‘irrational’ individuals, or to make sure that they understood the question:

Suppose you are offered two ways to earn some money. With option 1, you are guaranteed Rp800 thousand per month. With option 2, you have an equal chance of either the same income, Rp800 thousand per month, or, if you are lucky, Rp1.6 million per month, which is more. Which option will you choose?

By the way, the questions were asked to adult individuals, and there are around 29 thousand of them in this category. If the respondent answered (1), the interviewers would make sure if they stood by their choice or wanted to switch. Even after the follow-up question, 42 percent respondents are 'irrational' - meaning they opted for a certain Rp800 thousand, even if the other option would not make them worse off. The number, for me, is too high and will pose a serious potential bias in the analysis.

After completing a series of further questions, the 'rational' individuals are categorized into for groups, from the most risk-averse to the most risk-loving. Half of them belong to the most risk-averse group; about a quarter are most risk-loving, 14 percent are somewhat risk-loving, and less than 10 percent are somewhat risk-averse (see picture). The distribution implies that the variations across group are quite small, which lead to a question whether we can see an interesting story from that.

And there are some other concerns I got from various discussions:

• Since these are not true experiments but hypothetical, the noise may be big to infer anything.
• These are hypothetical risk question about money/income. But people may have a different answer if it involves health. So applying this type of gamble to health behavior may not be correct.

It is too early to kill of the topic completely, but it does not give me an 'Eureka moment' either. So I am now shopping for another possible topic.

Choices of State Intervention

Philip Musgrove, in Health Economics in Development (2004, chapter 2) wrote:

It matters not only whether government intervene, but also how they do it: the second essential question is what the public sector should do, given that some problem in the private market appears to warrant some public action.

And here are five alternative instruments of public sector, arranged from the least to the greatest intrusion into private decisions:

1. Inform, which may mean to persuade, but does not require anyone to do anything.
2. Regulate, which determines how a private activity may be undertaken.
3. Mandate, which obligates someone to do something and (usually, but not always) to pay for it.
4. Finance health care with public funds.
5. Provide or deliver services, using publicly-owned facilities and civil service staffs.

Health capital and demand for health

Michael Grossman (1972)* paper is perhaps the first attempt to develop a formal model of individual demand for health. Build upon Becker's human capital framework (1964, 1965, 1967), he treated health as a form of human capital stock, which depreciates by age, but can be increased by investment. Here's the abstract of the paper:

The aim of this study is to construct a model of the demand for the commodity "good health." The central proposition of the model is that health can be viewed as a durable capital stock that produces an output of healthy time. It is assumed that individuals inherit an initial stock of health that depreciates with age and can be increased by investment. In this framework, the "shadow price" of health depends on many other variables besides the price of medical care. It is shown that the shadow price rises with age if the rate of depreciation on the stock of health rises over the life cycle and falls with education if more educated people are more efficient producers of health. Of particular importance is the conclusion that, under certain conditions, an increase in the shadow price may simultaneously reduce the quantity of health demanded and increase the quantity of medical care demanded.

*Grossman, Michael, "On the Concept of Health Capital and the Demand for Health," The Journal of Political Economy, Vol. 80, No. 2 (Mar. - Apr., 1972), pp. 223-255.

Clear diagnosis, uncertain remedy

The Economist's article on problems and obstacles in reforming health insurance system.

Possible topic#2 - Risk Preference, Time Preference and Health-related Decisions

Second attempt. So the motivations are:

• Developing countries have lower quality of health: lower life expectancy, higher infant (and adult) mortality rate, etc. Is it because of supply constraint (availability of public services)? Household budget constraint? Or because people value ‘good health’ less?
• Budget constraints causes households or individuals highly prefers today’s income than long-term human capital investment (high discount rate). This could lead to fewer amount of HH budget allocated for own and/or children’s health
• Lower valuation of future health means individuals would engage in riskier health behavior, such as smoking, less exercise, bad dietary habit, not having health insurance
• Policy relevance: a) if risk and time preference do explain less investment on health and riskier behavior, then policies that promote changes in behavior/valuation will be relevant, b) otherwise, improving income/well-being will be the more relevant approach.

Fortunately, new set of questions in IFLS-4 enables to do the analysis of individual's risk preference and discount rate. Discount rate could me measured using questions on whether the respondent prefers a lower amount of money now or a higher amount one year (five years) later. Risk preference coefficients can be calculated from hypothetical questions of a choice between a job that guarantees a certain amount of lifetime income, and another job that gives the individual a 50-50 chance of a getting a higher or lower amount than the previous one.

Once the discount rate is constructed, I can use it as one of the explanatory variables for parent's (mother's) investment in their children's health. The underlying hypothesis is higher discount rate explains lower investment in health.

There will be two main groups of individuals to analyze. The first one is pregnant women. The particular variables to analyze are: 1) number of months of elapsed pregnancy before going to the health service, 2) smoking behavior during pregnancy, and 3) utilization/number of visits to health service during pregnancy. The second group will be children aged 5-15 years, whose variables of interest are their immunization record (completion, delays), utilization of health services and anthropometric measures.

Risk preference coefficient will be used to analyze individual's health-related risky decisions. Focusing on adults, the variables of interests are smoking habit, utilization of preventive health care, access to health insurance, Body Mass Index (a proxy for health status, which is the outcome of behavior, and possibly eating habit. The underlying hypothesis is that higher individual's risk preference lead to riskier health behavior.

Update: supervisor kind of like this idea. She thought this is an interesting topic. One concern is whether I could get enough variations in the data to lead to something. We'll see.

Why medical care market is different?

Like Muskin (1958), Kenneth Arrow's 1963 paper* is also considered as a pioneer in analyzing health issues using economic perspectives. In the paper, Arrow explained some special characteristics that make medical (health) care market different from the other markets:

1. The nature of demand. Demand for medical services is irregular and unpredictable. Medical services, apart from preventive services, afford satisfaction only in the event of illness, a departure from the normal state of affairs.
2. Expected behavior of the Physician. A physician's behavior is supposed to be governed by a concern for the customer's (patient's) welfare, and regulated by a certain ethical codes, more than other profession.
3. Product uncertainty. One consumes a medical service in expectation of recovery from illness. However, when we consume a medical service, we can not predict whether it will result in a recovery (and if it does, how long will it take).
4. Supply conditions. Entry to the medical profession is restricted by licensing. It means supply is limited, hence increasing cost.
5. Pricing. The nature of medical service enables seller to effectively (and extensively) discriminate price by, among other things, consumer's income.

For sure, it doesn't mean that medical care market is the only market with special characteristics. Financial, labor, credit, and many other markets have different characteristics that depart from traditional, text-book competitive market.

*Kenneth J. Arrow, "Uncertainty and the Welfare Economics of Medical Care," The American Economic Review 53(5):940-73.

What is health economics?

Selma Mushkin's paper (1958)* is probably one of the first papers mentioning the definition of health economics, and marked the boundary of health economics as a sub-discipline:

Health economics is concerned with the optimum use of scarce economic resources for the care of the sick and the promotion of health, taking into account competing uses of these resources. The basic problems are of two kinds: the organization of the medical market, and the net yield of investment in people for health.

Moreover, Mushkin explained why health economics merits becoming an sub-field:

Consumer preferences are not an adequate guide to the optimum allocation of resourcesfor health. There are a number of reasons why this is so. For one thing, a consumer would prefer to avoid the illnesses which require use of resources for health purposes. For another, his neighbors benefit from the medical services he purchases, for example,"flu shots" during the recent influenza epidemic. Individual decisions undervalue health services, and would result in under production of these services unless supplemented by actions of private voluntary agencies and government.

Of course, the field has been developing since 1958, and the coverage of study has been largely expanding.

*Selma Mushkin, "Towards a Definition of Health Economics," Public Health Reports, 1958, 73, 785-93.