What the new Health Law does not do

Responding to my Jakarta Post op-ed article, two colleagues of mine Arya Gaduh and Puspa Amri raised some important points. Arya mentioned this book, and he pointed out the health reform might ignore some of the lessons from the study. He also raised a more fundamental question: will universal coverage improve health outcomes? Not so much, according to the research.

Puspa reminded me that the new Law touches very little, if nothing, on curbing the ever-increasing health cost. I admit, I overlooked this issue. Some of the measures were dropped earlier in the bargaining process. Lobbyists may have some roles, as this article suggests.

Thanks, mates!

Understanding the US health care debate (3)

Part III. The politics and controversies

The first part of the saga has just ended. President Obama finally signed the new Health Law, after the Congress earlier approved the Bill. The Law will be a major landmark for the Obama administration to push their health care reform.

With a 53% popular vote in the presidential election and a Democrat majority in both chambers of the Congress, pushing the reform seemed to be an easy job for Obama. In reality, it hasn’t been so. Republicans has pledged to block the reform, at least make it a hard-to-win battle.

Separating signal from the noise, the Republicans points were: 1) rejecting the establishment of a government-run commercial insurance which they argued will crowd-out the private insurance market, 2) allowing interstate competition of insurance companies, 3) reforming malpractice law, which had threatened doctors and hospitals with big lawsuit compensations, 4) a less costly reform involving less or no tax increase, but far fewer people would be covered by insurance. Plus some traditional Republicans issues like limiting illegal immigrants from purchasing government-funded insurance and prohibiting Federal money to finance abortion.

Learning from Clinton’s 1993 failure, Obama distanced himself (and the White House) from the micromanagement. He let the Democrats in Congress got bogged down in the details and wrestled with the opponents.

In November 2009, the House announced their version of the Bill. The version was a 1,990-page long. Many believed this version would be difficult to win. The Economist described the earlier version of the Bill as ‘soaking the rich.’ It was estimated to cost the government around US$1.5 trillion for the next 10 years, more than $1 trillion limit set by Obama. Moreover, it was not budget-neutral. It would add $239 billion to the deficit, although it included a tax increase for business with more than $250,000 per year in payroll and individuals earned more than US$350,000 a year. Plus a steep ‘surcharge’ for the wealthy.

Before Christmas, Senate came up with their version (the one which will later become the Law, with some adjustments). The procedure in the Congress requires both chambers to agree on an identical version of the Bill. This means both House and Senate would need to work on a new, merged version before going back to the voting process. The Bill is said to cost US$940 billion for the next decade, and the impact on budget deficit is US$138 lower than the baseline scenario. It aims to provide cover for 32 million out of 47 million uninsured by 2019. Still not a universal coverage, but coverage rate will increase from 85% to 94%.

Until December, this still looked to be an easy process. With a 60-seat supermajority in the Senate, Republicans would not be able to block the Bill through filibuster – keep delaying the vote on and on by continue debating a bill. But in January, Scott Brown won the Massachusetts Senate seat vacated by the late Ted Kennedy. This made him the 41^st Republican in the Senate, eliminating Democrat’s supermajority power.

Obama and his party had to switch strategy. Instead of working on a merged Bill, the House would vote for the Senate version. In this case, only 51 votes (simple majority) will be required in Senate. Later they would be able to tweak some of the clauses through what is called ‘budget reconciliation’ process. (This strategy enraged Republicans. But in truth, both parties had used this in the past.)

In February, the Obama revealed their version of the Bill, after a gathering called ‘bipartisan summit’. Practically, it was similar to the Senate Bill, except for some minor clauses regarding fines for individuals not having insurance. Later Obama also asked Harry Reid, Senate Democratic Leader and Nancy Pelosi, House speaker, to ‘consider’ some Republicans ideas: malpractice law reform and an oversee board for insurance fraud.

But the Democrats also needed to deal with internal challenges. Conservative Democrats rejected the idea that Federal money could be used to finance abortions. Democratic Hispanic Caucus concerned if illegal immigrants would be barred to purchase government insurance using their own money. On the other hand, left-wing Democrats questioned why the Bill does not contain establishing a public or government-run insurance company.

The internal lobby still took place until the last minute before the voting took place on Sunday, March 21. But in the end 219 voted ‘yes’, while 212 – all 178 Republicans and 34 Democrats – voted ‘no.’ (Many gave the biggest credit to Nancy Pelosi). The next step was mere formality. The Senate passed the bill, and in March 23 Obama signed the Bill into Law.

The Law is only the first test for the reform. The Obama administration will face other big tests. How fast the administration could start the reform (and how feasible it is in practice). Will the reform cost not blow out of what was estimated? And, more importantly, will it improve the health indicators? Not to mention another battle with the Republicans, and the states.

See also: The new Health Law, what will it do?

Readings on Indonesia's health sector

Two good reports by the World Bank: Investing in Indonesia's Health (2008) and Health Financing in Indonesia: a Reform Road Map (recent).

The new Health Law, what will it do?

Immediate benefits:

• Insurance companies are prohibited to impose annual or lifetime caps.
• US$5 billion funds are pledged to provide temporary coverage for uninsured individuals with pre-existing conditions.
• Children can stay on their parents’ health insurance until they turn 26.
• Drug discount for seniors.

By 2014:

• All US residents is required to have health insurance, or face a fine of up to US$95 or 1% of their annual income in 2014, gradually increase to US$695 or 2.5% of their annual income.
• A health insurance exchange will help small businesses negotiate with insurance companies.
• Medicaid expansion and tax break for families.

By 2019:

• Expand medical insurance coverage to 32 million.

Source: CNN. See more details here and here.

The new health care bill

The new bill looks to become law after the House voted to pass the Senate version. I am working on part III of my 'Understanding the US health care debate' series, which will include the current politics and result.

In the meantime, here's a good post by Greg Mankiw. Don't mean to spoil the party, but always good to have someone reminding not too get too drunk after a party. The bottom line is every choice has its trade-off. The challenge for policy people is how to minimize the trade-off.

Understanding the US health care debate (2)

Part II. Earlier attempts to fix the system

Many initiatives and proposed solutions to the health care system have been revolving around increasing coverage and reducing costs (see my earlier post about the problems). Options for increasing coverage include mandating individuals to purchase health insurance (and imposing a fee for those who opt not to), usually combined with subsidies for the poor, and providing tax-incentives. Many analysts and politicians believe the US should have an individual mandate. Without it, many young, healthy individuals may choose to be uninsured, means the average health among the pool of insured will go down, hence insurance premium will stay high or go higher.

Attempts to reduce cost range from introducing more competition to the insurance and health care market, imposing a cap on price, limiting what medical procedures that the government would reimburse, to introducing more complex and bureaucratic regulations or regulatory bodies.

The New York Times has a nice interactive timeline of the comprehensive history of US health care reform. I

Clinton's 1993 proposal

Introduced by President Bill Clinton, efforts was led by First Lady Hillary Clinton, who chaired the National Task Force (hence the nickname Hillarycare dubbed by the opponents). The key components of the plan were:

1. Mandating all eligible U.S. citizens to purchase health care, and employers of all businesses and all sizes, to provide insurance for their workers.
2. Standardizing benefits - the plan listed minimum coverages and maximum annual out-of-pocket expenses for each plan.
3. Establish a National Health Board in charge of regulating all health care in the country.

The proposal, as we know it, failed. Many possible explanations on why it failed. But the most common arguments are it was too complex, too ambitious, and lack of incrementalism - although moving to single-payer system, oddly, was not part of the plan. Later in 2000, Mrs. Clinton remarked that the US needs a more step-by-step approach in achieving universal coverage.

Partisan politics have off course contributed, though many analysts said that supports from Democrats grassroots were not too solid anyway. Then there was also resistance from the big pharmaceutical companies. Plus, an economic dip in the early days of the administration did not help. But the Clintons were also criticized for their lack of efforts in reaching out to the opponents and making the plan simpler for the wider audience.

Massachusetts 2006 reform

In 2006, the Commonwealth of Massachusetts enacted a Law that requires nearly every resident to obtain health insurance. Through the Law, the Commonwealth government also provides free health care and partial subsidies for low-income residents. The Law was a result of a bipartisan coalition. However, the original proposal was initiated by then governor and 2008 Republican primaries candidate Mitt Romney.

Another aspect of the plan is the creation of a health insurance “exchange.” Basically, it was a clearing house to help small firms from conducting complex negotiations with insurers. Employees will be able to choose any plan approved by the state-backed exchange, and their premiums will be deducted from their pay checks.

From Fall 2006 to Fall 2007, the number of uninsured among low-income adults dropped from 24% to 13%, while among the higher income the number dropped from 5% to 3%. As of 2008, overall rate of uninsured has dropped further to 2.6%. The Massachusetts reform has been widely referred to as the model for the national-level reform by both Clinton and Obama during the 2008 Democratic primaries (although it did not provide enough leverage for Mitt Romney himself).

However, it was not immune from criticisms. It has strained the state budget, and a future budget crisis may be a consequence, failed to reduce medical spending, has subsequently drawn funding away from crucial health resources such as emergency room care, in practice the plan is not affordable for many families, and increased queues for already crowded medical services.

Some smaller attempts

A bipartisan Patient's Bill of Right, articulating a list of positive rights which doctors and hospitals ought to provide patients, thereby providing information, offering fair treatment, and granting them autonomy over medical decisions, was debated in Congress, but failed to pass as a Law. In 2003, President George W. Bush signed a Law that expanded Medicare to cover prescription drugs. Health care reform was one of the issues during Bush-Kerry 2004 debate. But in his second term, there was no major initiatives. Instead, the Bush administration was locked in a heated debate on reforming the country's social security.

The 2008 presidential campaign

John McCain's proposal was in fact closer to traditional Democrat's position than many Republicans. He supported importing drugs from Canada, which should make him an enemy of the pharmaceutical industry. He wanted Medicare to negotiate bulk discounts with the industry, which was always opposed by the Republicans.

The differences were, first, instead of mandating individual, he proposed to give tax credits as incentives for individuals to purchase health insurance.

Second, to curb the overuse of technology and needless medical procedures, he wanted to change the incentives by scrapping payments for individual procedures in favour of giving fixed payments to doctors and hospitals for actually solving particular health problems.

Third, he also wanted to impose caps on damages for malpractice and rule out awards for punitive damages - something that would put him into a war with the lawyers.

In many ways, candidates Clinton and Obama's proposals were quite similar. Both proposals offered Massachusetts-like mandate-and-subsidy schemes. Both plans would also force insurance companies to provide coverage for all (for example, by making it illegal to turn down new applicants with pre-existing medical problems). Particularly for Clinton, hers was a substantial simplification of the 1993 ambitious plan.

The differences between those two were, first, Clinton's plan would require all individuals to have health insurance, while Obama's would only require children, hence his was less ambitious in achieving the universal coverage.

Second, Clinton planned to oblige all firms in all types and all industries to provide covers for their employees. She would also introduce a tax-break reform for employer-based coverage but small firms would be subsidized. Under Obama's plan, firms would also be required to provide insurance for their workers, but small firms would be exempted, and tax-break reform was not part of his proposal.

Bear in mind that these were their proposals as candidates. There is a big gap between the campaign and the White House version, as shown in history. They'd need to face battle with the Capitol Hill, as well as do reality checks. President Obama's health care plan has not been revealed until after a year. When it was finally revealed, it was not a clear one, while at least two versions of the bill, one by the House, the other - a stronger one - by the Senate, have been introduced. And the battle continues.

Understanding the US health care debate (1)

I am not an expert on the US health system, and at best I am remotely trying to follow the latest health care reform issues. So what I would write here will reflect my very basic and overly simplified understanding of the issue. There are some reasons why the current debate on the US health care reform is interesting as well as important to monitor.

First, it will be the biggest domestic policy test for the Obama’s administration. How it goes, and how it ends, will affect the support and legitimacy of the administration, and perhaps determine the fate of it. Second, depends on what version of the bill comes out in the end, it could be one of the biggest changes in a country’s health and insurance system in history. Third, it is a high-profile case on how ideology, pragmatism and day-to-day politics simultaneously affect the outcome of a policy. Some people would like to see this as a fight between the market and government-oriented, Democrat and Republicans. But the truth, it is much more complex than that. Fourth, Indonesians can learn from this process, from the debate, outcome and implementation, including the trade-offs of making one policy choice over another.

There are three major areas of the debate: the problem with the current US health care system, the proposed solutions, and the politics. The order of those three also somewhat reflects the degree of my understanding, from the most to the least.

Part I. The problem

The US health system faces two main problems: 1) a very high percentage of people are not covered by health insurance (with a high proportion of those with insurance are underinsured), 2) high and rising insurance and medical cost. These two are highly related to each other so it is difficult to disentangle what causes what. They also face other challenges: how to solve those two problems with minimal cost (means how not to increase the budget deficit and/or introducing more taxes), and without hampering health and medical innovations.

Coverage

The Economist frequently cited that in 2009 some 47 million US residents (around 15% of the population) are uninsured. This is slightly higher than 46.3 million in 2008 and 45.7 million in 2007. In 2007, 37 million of the insurance are working-age adults, with 27 million working at least part time.

High price is the main reason why they are uninsured. Individuals from low-income households are more likely to be uninsured. But high cost also drives individuals who could afford to buy opt to not purchasing one. The problem is they are the more healthy ones. This lowers the average health among the pool of insured individuals, raising the premium, hence drives the overall cost up.

But many private insurance companies also turn down ‘risky’ applicants; for example, those with pre-existing health problems, risky lifestyle or environment. Some people point this as discrimination, because individuals with risky environment tend to come from minority race, especially Latinos. In fact, more than 30% Latinos are uninsured, compared to 10% of white, non-Latinos.

Of the 85% individuals who have some kind of health insurance, 60% receive it through their employers (or employers of their spouses, partners or other family members). That means many individuals will lose their insurance if they or their family bread-makers lose their jobs. Some 9% purchase health insurance individually.

The government also provide health insurance through several schemes (Medicare, Medicaid, SCHIP, TRICARE, IHS and some state-provided ones). Public health insurance schemes provide coverage to some 28% Americans – there are some overlaps between the public and private coverage.

Cost

By far, the US health care system is the most expensive in the world. In 2007, total health expenditure accounts for 16% of GDP; other developed countries spend no more than 11% of their GDP. In the same year, the US spends $7,400 per person on health care. Around half of the spending goes to hospital care (31%) and physician/clinical service (21%). Ironically, with that level of spending, the US is one of the worst among developed countries in terms of health indicators.

What drives the health care cost? According to Kaiseredu.org, rising costs of medical technology and prescription drugs and high administrative costs (e.g. marketing, billing, which accounts for 7% of total cost) contribute from the supply side. On the one hand, technological progress has made the US health system is perhaps the most innovative and advanced in the world. But it means the consumer needs to bear some of the investment cost. On the other hand, this has also made the industry become more and more supply-driven; they generate demand for more intense and costly services, though not necessarily more effective. Similar story happens with the pharmaceutical industry.

From the demand or consumer’s side, demographic changes that have occurred over the past century have resulted in higher life expectancy, older population but also new, more complex health problems. Prevalence of chronic lifestyle-related illnesses has increased substantially.

Another contributing factor, although the relative contribution is still debatable, the legal process-related costs. According to one estimate, Medical malpractice lawsuit accounts for 5-10% of total medical cost each year. Medical service providers, facing high financial and reputation costs, are then ‘forced’ to perform extra procedures for patients.

There are also arguments pointing out that rising health care costs have been driven by the public insurance scheme (Medicare, Medicaid etc.). They are lack of competition, and the reimbursement system has created perverse incentives for medical care providers (see this or this). The other side of the argument blame more on private insurance companies because they have been overcharging consumers, so a cap on insurance premium needs to be introduced.

Missing women, again

It is often said that women make up a majority of the world's population. They do not. This mistaken belief is based on generalizing from the contemporary situation in Europe and North America, where the ratio of women to men is typically around 1.05 or 1.06, or higher. In South Asia, West Asia, and China, the ratio of women to men can be as low as 0.94, or even lower, and it varies widely elsewhere in Asia, in Africa, and in Latin America. How can we understand and explain these differences, and react to them?

-- Amartya Sen, More than 100 million women were missing,

editorial article from The New York Review of Books, December 20, 1990.

This week's The Economist published a special report on the growing worldwide gender imbalance at birth, especially in some developing countries. For example, the article cited:

In China the sex ratio for the generation born between 1985 and 1989 was 108, already just outside the natural range. For the generation born in 2000-04, it was 124 (ie, 124 boys were born in those years for every 100 girls). According to CASS the ratio today is 123 boys per 100 girls.

As the consequence, within ten years one in five young men would be unable to find a bride because of the dearth of young women—a figure unprecedented in a country at peace.

What caused the highly skewed ratio? According to the article, it is the combination of 1) parents' strong preference over boys (for whatever reasons - economic or cultural), 2) declining fertility, either by policy or improved income, so nowadays parents tend to have a limited number of children, and 3) advanced in technology; cheaper ultrasound makes it possible to detect gender of fetus, hence parents might decide to abort the unborn if it was a girl ('Gendercide', as the article refers to it).

The article also linked this trend to socio-cultural changes, including problems. In a highly homogeneous Korea, inter-country marriage becomes more common and acceptable. In some parts of India, a bride can only marry a man from a different village if the groom's village provides another bride in exchange. In China, growing number of unmarried men has created pressure to crime and violence.

* * *

Skewed male-female ratio in developing countries has been an interest for long. The cited paragraph in the beginning was a summary of a series of papers Sen has written in the 1980s.

Where did the number come from? Let's take 1.05 as the 'normal' ratio of women to men.¹ It means that if a country like China has a ratio of 0.94, this alone amounted to more than 50 million deficit of women. Together with the female deficit in South Asia, Africa, and other developing countries, they added up to more than 100 million.²

The reason, as Sen argued, was 'discrimination' against girls in getting access to health care, medicine and nutrition. The term 'discrimination' here should be treated carefully. It may not be a clear case of discrimination, but different intra-household preference in allocating resources towards boys and girls, resulting in higher mortality rate of women compared to men.³

Some researchers have tried to come up with different explanations for the missing women. Emily Oster (2005) argued, Hepatitis-B could be one explanations. Unborn boys have more chance to survive if their mothers have Hep-B. High prevalence of Hep-B among pregnant mothers in those countries skews the gender ratio at birth towards boys. The missing girls were not missing, concluded Oster; they were never born at all. However, her later study in China with Gang Chen (2008) didn't show that Hep-B explains male-biased sex ratio. So the Hep-B hypothesis may still be doubtful.

That makes selective abortion, as reported in The Economist article, the likeliest. possible explanation, for now. Amartya Sen seems to agree. As he wrote in his 2003 article, revisiting his earlier one:

But another more important and radical change has occurred over the past decade.T here have been two opposite movements: female disadvantage in mortality has typically been reduced substantially, but this has been counterbalanced by a new female disadvantage—that in natality—through sex specific abortions aimed against the female fetus. The availability of modern techniques to determine the sex of the fetus has made such sex selective abortion possible and easy, and it is being widely used in many societies.

¹ Sen defined gender ratio as the number of women divided by men. Many (most?) other calculation define it as the other way round, multiplied by a hundred. So a ratio 0f 106 means for every 100 women there are 106 men. Doesn't matter which one we prefers as long as we know what it is.

² Using slightly different method, Klassen and Wink (2003) estimated a lower - but still large - number of 'missing' women, 89 million.

³See a paper by Monica DasGupta (1997) on how boys and girls received different allocations of health and nutrition, based on a survey data from India.

Investing in nutrition in developing countries

Why? Well, the answers are quite clear. As a form of human capital, nutrition affects individual productivity both directly (through greater ability to work) and indirectly (through cognitive and educational achievements).

The question for empirical researchers is: how do we know? Higher wages and income clearly increase demand for nutrition, and so do higher education (endogeneity bias). And it is also possible that a third variable simultaneously affect nutrition and income (omitted variable bias). Schultz (2003) pointed out these issues.

But many studies have tried to overcome those problems, using experimental, quasi-experimental or instrumental variables. Behrman (1993), also Thomas and Frankenberg (2002) documented those studies. One of the most widely cited experimental study is The Work and Iron Status Evaluation by Thomas et al. (2006).

Geography, sanitation and diarrhea

I've been involved as a research assistant for a study on sanitation project in rural East Java. One of the tasks was supervising the data collection from more than 2,000 households in 160 villages in 8 districts (kabupaten) in East Java, between August and December 2008.

The most important information we'd want to collect is whether the household has access to 'improved sanitation.' Improved sanitation is based on an international definition. Basically, if the sanitation facility is just an open pit, open area or riverside, then it is 'unimproved.'

When I did the calculation of the percentage of households^* with improved sanitation by district, I found a quite obvious geographical pattern. People in the Western part of East Java has higher rate of improved sanitation compared with those in the Eastern part. This could be due to different climate and soil type. But what is interesting for me is the geographical boundary also coincides with cultural boundary. The Western East Java are of 'Mataraman' sub-culture - with closer proximity to the Central Javanese. The Eastern side are predominantly Madurese, they don't even speak Javanese in that part.

Could culture explain the variation in sanitation behavior? Too early to conclude, since so many variables may interact with each other. But this could be a starting point to look further.

What is clear is there is a correlation between improved sanitation and diarrhea incidence among children under five. This suggests that an intervention aims to improve sanitation quality could be an effective measure to reduce diarrhea prevalence for children, among other illness.

The question is: how. The project in which I involved specifically deals with creating demand for improved sanitation through community-based promotion. It is not a subsidy or supply-side intervention. Is it effective? Ask me again by the end of the year when we are (supposedly) done with the study.

^*Due to copy right issue I can not share the numbers here. Sorry.

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.

Discarded Topic#1

Update: Possible Topic#1 is now Discarded Topic#1. Supervisor didn't agree, on the basis that 'they have been written for too many times. Oh, well.

Possible topic#1 - Health, Nutrition and Rural Household Welfare

Some motivations for looking at the link between health, nutrition and the welfare of rural households:

• Health and nutrition are important aspects of basic needs, while one of the main goals of economic development is to expand the capacity to obtain basic needs, especially for the poor people.
• The productivity of low-income people is strongly correlated with improved health and nutrition.
• Improving health and nutrition are important means in itself, as well as an instrument for improving welfare.

Behrman and Deolalikar in Handbook of Development Economics (1988) provided a good framework to start with. It is a modified household-farm decision making model, which was based on earlier works by Barnum and Squire (1979) and Singh, Squire and Strauss (1986).

Based on this, I intend to look at three specific issues:

1. Household demand function and income elasticity of nutrient (calorie).
2. Estimating the return of improved nutrient intake (calorie) and health status (Body Mass Index, anthropometric measures), evaluated in terms of: a) farm profit, b) individual wages, and c) output/productivity
3. Estimating the impact of healthy environment (clean water, improved sanitation) on children health status (as a proxy for human capital accumulation).

Why health and development economics?

Having studied economics as an undergraduate at the University of Indonesia, I learned how people respond to incentives in making their personal choices. That includes choices in fertility preference, health behavior and risky decision (ranging from dietary to sexual behaviors). Then, having a Master’s degree in Public Administration/International Development from Harvard, I learned further that privately optimal decisions may not be socially optimal. In the context of developing world, this situation is translated in underinvestment in human capital (too many children, lack of nutrition and education).

My professional experiences have facilitated me to understand more about public health problems in the developing countries through empirical works. Before coming to Harvard, I worked as an economic researcher in an Indonesian research institute. I focused on poverty, income distribution and social policy issues. After receiving my Master’s degree, I worked for the Poverty team in the Indonesian office of the World Bank. I have never specifically focused on health policy issues. But I found close relations between income poverty and poor health conditions. Poor people are lacking of access to basic health services, clean water and sanitation; and poor health results in low productivity which in the end leads to poverty.

Finally, being a parent of a one-year old baby girl means a real world application of the theories about health decisions: from immunization and nutrition decision to household decision making (how my wife and I bargain on who do the babysitting or how to raise her), and changing pattern of household spending (given the same level of income we should sacrifice our expenses for movies, coffees and dinner out). For the next few years, she will be my own ‘real world (but non-random) experiment.’

This particular question especially motivates me to do Ph.D. research in health and development economics: how to improve the quality and accessibility of health care for poor people in developing countries. It is a challenging as well as interesting issue, as it lies on the intersection of economics, health, demography and public policy in the context of economic development, particularly in Indonesia where I am most familiar with.

Quality and accessibility of health care is one big problem in a developing country like Indonesia. The country’s maternal mortality rate is three times that of Vietnam and six times of China and Malaysia, with 28 percent of births are accompanied by unskilled or traditional birth attendants. Malnutrition rates are also high. About a quarter of children under five are malnourished. On the other hand, although public health spending has been increasing, it is getting les pro-poor. Forty percent of health budget is allocated to subsidies for government hospitals (secondary care). However, most of the Indonesia poor do not use hospitals but go to primary care (community health care, midwives, immunization or village nutrition centers).

Reforming the country’s health care system should achieve two big goals: i) providing greater public investment for primary health care which are used mainly by the poor, and ii) increasing the utilization of secondary healthcare among the poor. To achieve the goals, three policy area should be prioritized. First, increase the budget for, as well as improve the quality and targeting of, primary healthcare provision. That includes also tackling the absenteeism problem among paramedics. Second, invest in demand-side activities that increase the access of the poor to secondary care, through schemes such as health card. And third, invest in the training of private paramedics and subsidize them through voucher schemes, especially in rural areas where the poor have little access to services.

Welcome

Welcome to this blog, and thanks for coming.

The idea behind this blog is to document the progress of my dissertation from the very early stage. That includes what ideas for topic I encounter, methods, other general knowledge I learn, articles or books I read, and even some random stuffs that might appear. Some of the ideas I found in the way may end up being not what I want or can write. But they still may be too good to be trashed.

The title of this blog, as you can see, is Health and Development Economics. That reflects the field I am intending to work, and specialize, on.