Andrew Leigh

For not-so-surprising reasons, I’ve been thinking lately about lifecycles. My AFR op-ed today (partially written with a newborn babe in the crook of my arm) is on age and creativity. Full text over the fold.

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Alison Booth, Elena Varganova and I have just released a study comprising three experiments to gauge racial and ethnic discrimination in Australia.

Does Racial and Ethnic Discrimination Vary Across Minority Groups? Evidence From Three Experiments
Alison Booth, Andrew Leigh & Elena Varganova
We conducted several large-scale field experiments to measure labor market discrimination across different minority groups in Australia – a country where one quarter of the population was born overseas. To denote ethnicity, we used distinctively Anglo-Saxon, Indigenous, Italian, Chinese, and Middle Eastern names, and our goal was a comparison across multiple ethnic groups rather than focusing on a single minority as in most other studies. Our main experiment, an audit discrimination study, involved sending over 4000 fictional resumes to employers in response to job advertisements. In all cases, we applied for entry-level jobs and submitted a CV showing that the candidate had attended high school in Australia. We found economically and statistically significant differences in callback rates, suggesting that ethnic minority candidates would need to apply for more jobs in order to receive the same number of interviews. These differences vary systematically across groups, with Italians (a more established migrant group) suffering less discrimination than Chinese and Middle Easterners (who have typically arrived more recently). We also conducted two additional experiments to form a more nuanced picture of prejudice. These were a ‘Return to Sender’ experiment and an Implicit Association Test. The results from both experiments reveal societal prejudice against minority groups, although the ranking sometimes differs from that in the audit discrimination study.

(see also a media release, brief summary of results)

A few words about each of the experiments.

The Jobseeker Study

There were several things that surprised me about the jobseeking experiment:

• Indigenous applicants seem to face less discrimination at the interview stage than Chinese or Middle Eastern applicants. To get the same number of interviews as an applicant with an Anglo-Saxon name, a Chinese applicant must submit 68% more applications, a Middle Eastern applicant must submit 64% more applications, an Indigenous applicant must submit 35% more applications, and an Italian applicant must submit 12% more applications.
• Discrimination against Chinese and Middle Eastern jobseekers is highest in Sydney, and lowest in Brisbane. As a Sydneysider, this rather dispelled my notion of tolerant Sydney vs redneck Brissie, but it’s entirely consistent with the literature on migration threat, which finds that an influx of migrants increases prejudice. In the long-term, Sydney may end up more tolerant, but the short-term effect of being the number one destination for immigrants is a rise in prejudice.
• Even in data-entry jobs, there is substantial discrimination against non-Anglo applicants. This indicates that it can’t just be customer-based discrimination, but must be either driven by coworker or employer biases.

For some real-world evidence to back up the results of the first experiment, here’s a quote from one jobseeker:

“After completing TAFE in 2005 I applied for many junior positions where no experience in sales was needed – even though I had worked for two years as a junior sales clerk. I didn’t receive any calls so I decided to legally change my name to Gabriella Hannah. I applied for the same jobs and got a call 30 minutes later.”
~ Gabriella Hannah, formerly Ragda Ali, Sydney

The chart below shows how Australian discrimination in 2007 compares with similar studies that have been done in other places and at other times. The way to read the vertical axis is that 1 means the minority candidate must submit just as many more applications to get the same number of interviews, 1.5 means the minority candidate must submit 50% more applications to get the same number of interviews, and 2 means the minority candidate must submit twice as many applications to get the same number of interviews.

So it’s worse to be Middle Eastern in Australia in 2007 than in Sweden in 2005, but it’s better to be Indigenous in Australia in 2007 than African-American in the US in 2001. Comparing our results with the 1986 study, it doesn’t look as though discrimination in Australia has fallen over time.

The Return to Sender Experiment

The second experiment was a return-to-sender experiment (a suggestion of my wife). By sending out mis-addressed letters to over 2000 Australian households, we effectively give them two options: to return the letter (costly, but the right thing to do), or put it in the bin (cheap, but slightly naughty). On average, 53% of letters with Anglo names were returned, but only 48-49% of letters with Chinese, Italian or Middle-Eastern names. In other words, 1/20th of Australian households would return a letter if it had an Anglo name, but not if it bore a Chinese, Italian or Middle-Eastern name.

The Implicit Association Test

I’m particularly indebted to the blogosphere for help on the third experiment, which is an Implicit Association Test (anyone who is curious can still take it at http://iat.org.au/). Among the bloggers who kindly directed readers towards the IAT were Larvartus Prodeo, Core Economics, Possum Pollytics, Andrew Norton, Ambit Gambit, Oz Politics, and Club Troppo.

Of course, those who read blogs aren’t a representative sample of Australians, so we reweighted the sample in two ways. The first is pretty standard – we just created demographic weights (making the age-sex-education-birthplace composition of the sample match the general population). But our second technique was more novel: we asked all IAT respondents some questions about their explicit prejudice, and then created prejudice weights, exploiting the fact that the same questions were asked of a nationally-representative sample of respondents in the 2007 Australian Survey of Social Attitudes. So far as we know, we’re the first to have combined implicit and explicit prejudice in this way.

And the results of the IAT? While some people are pro-minority, the average respondent showed a subconscious bias against each of the four minority groups. Here’s the distribution.

Jeff Borland has a splendid article (gated, sorry) in the latest Australian Economic Review on what happens to the labour market in recessions. From it, I learned:

1. The impact across industries differs greatly. In past recessions, employment tends to fall in agriculture, manufacturing and construction, but also tends to rise in ‘recreation and personal services’, and sometimes also in the ‘community services’ industry.

2. In percentage point terms, youth unemployment tends to rise more than prime-aged unemployment in recessions, but the proportional increase is the same. For example, in the early-90s recession, unemployment rose from 10.4% to 18.4% for 15-24 year olds, and from 4.3% to 8.5% for 25-54 year olds. So both rates approximately doubled, but that represented an 8pp increase for kids, and a 4pp increase for adults.

3. In recessions, long term unemployment tends to increase more than short-term unemployment.

4. Unemployment inflows and outflows both increase. Jeff explains the puzzle.

The flows between employment and unemployment in Australia have followed a regular pattern during recessions and upswings. In particular, both tend to increase during recessions. It should not be surprising that the inflows to unemployment from employment increase during a recession, as this is a time when we expect many workers to lose jobs due to a reduction in demand for firms’ output. However, it might seem curious that the outflows from unemployment to employment also rise during a recession. How can it be that more people are finding jobs in recessions than upswings?

This phenomenon can be explained as follows. The magnitude of the outflows from unemployment to employment from one month to another depends on the number of persons who were unemployed in the initial month and on the probability that a person who was unemployed in that initial month shifts to employment by the next month. Even though the probability of an unemployed person moving to employment falls during recessions (that is, it becomes harder, on average, for any individual unemployed person to find a job), there is also a much larger number of unemployed persons during a recession, and it turns out that the effect of having more unemployed persons is the dominant effect on the magnitude of the flows from unemployment to employment. Hence, the outflows from unemployment to employment are at a peak during recessions.

This finding has quite important implications; for example, for agencies (such as Job Network providers) who are seeking to place unemployed persons into employment. It suggests that their total number of successful placements of unemployed clients into jobs is likely to be the highest during recessions.

5. According to 1997 time use data, 15-20% of unemployed people report job search activity on any given day, with the average time spend searching among those people being 80-100 minutes per day. Multiplying these numbers together, the average time spent job searching across all unemployed people is 16 minutes per day, or a little less than 2 hours per week.

If you can get access to the article, it’s highly recommended reading.

(xposted @ Core)

Michael Kortt and I have a descriptive paper in the 4th HILDA statistical report (pp180-187), discussing correlates of body size among Australian adults. A few snippets:

• Comparing across states and territories, we find relatively few systematic differences for men. However, there are some small differences for women, with women in South Australia and Western Australia about 1cm taller than the national average.  Women in Victoria are significantly less likely to be obese (20% compared to a national average of 23%), while women in the Northern Territory are significantly more likely to be underweight (9% compared to a national average of 3%).
• Comparing across generations, Generation Y (those born in 1976-85) are on average 3cm taller than Baby Boomers (those born in 1946-55). Even accounting for the recognised fact that people’s height shrinks slightly as they grow older, there does appear to have been a 1-2cm secular increase in the heights of men and women in Australia over time.
• There are large differences across education groups. On average, people with a bachelor degree are 2-3cm taller than respondents who did not complete high school. University graduates are also half as likely to be obese than people who did not complete high school.  However, some of this may be due to family background, since we also found that people whose fathers worked in high-status occupations tended to be taller and slimmer than respondents whose fathers worked in low-status occupations.
• Finally, we looked at the ethnic and racial correlates of body size. On average, men and women who were born overseas are 3cm shorter than those who were born in Australia. Immigrants are also less likely to be obese than those born in Australia. Comparing Indigenous and non-Indigenous respondents, there are significant racial differences in obesity for women, with the obesity rate being 22% for non-Indigenous women, and 34% for Indigenous women.

My oped today is on employee share ownership, drawing on a series of papers by Richard Freeman and his band of coauthors. Full text over the fold.

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In the context of the feisty share ownership debate, I thought it might be worth posting two 2008 economics papers on the topic.

My quick read of the evidence: employee ownership exposes workers to more risk (if the firm goes under you lose your job and your investments). For the firm, it has advantages, including less absenteeism, better morale, and higher productivity. It’s quite clear to me why firms like ESOPs, but less obvious that workers should love them.

Risk and Lack of Diversification under Employee Ownership and Shared Capitalism
Joseph R. Blasi, Douglas L. Kruse, Harry M. Markowitz
Some analysts view risk as the Achilles Heel of employee ownership and to some extent variable pay plans such as profit sharing and gainsharing. Workers in such "shared capitalist" firms may invest too much of their wealth in the firm, contrary to the principle of diversification. This paper addresses whether the risk in shared capitalism makes it unwise for most workers or whether the risk can be managed to limit much of the loss of utility from holding the extra risk. We create an index of financial security based on worker pay and wealth, and find that workers who feel financially insecure exhibit fewer of the positive outcomes associated with shared capitalism, and are less interested than other workers in receiving more employee ownership or even more profit sharing in their workplaces. This response is substantially lessened, however, when accounting for worker empowerment, good employee relations, and high-performance work bundles that appear to buffer worker response toward risk and increase interest in shared capitalism plans. We also discuss portfolio theory which suggests that any risky investment — including stock in one’s company — can be part of an efficient portfolio as long as the overall portfolio is properly diversified. We show that given estimates of risk aversion parameters, workers could prudently hold reasonable proportions of their assets in employee stock ownership of their firm with only a modest loss in utility due to risk. A good strategy for firms is to personalize individual portfolios on the basis of worker characteristics and preferences, developing investment strategies that would diversify each worker’s entire portfolio in ways consistent with individual risk preferences.

Creating a Bigger Pie? The Effects of Employee Ownership, Profit Sharing, and Stock Options on Workplace Performance
Joseph R. Blasi, Richard B. Freeman, Chris Mackin, Douglas L. Kruse
This paper uses data from NBER surveys of over 40,000 employees in hundreds of facilities in 14 firms and from employees on the 2002 and 2006 General Social Surveys to explore how shared compensation affects turnover, absenteeism, loyalty, worker effort, and other outcomes affecting workplace performance. The empirical analysis shows that shared capitalism has beneficial effects on all outcomes save for absenteeism and that it has its strongest effects on turnover, loyalty, and worker effort when it is combined with: a) high-performance work policies (employee involvement, training, and job security), b) low levels of supervision, and c) fixed wages that are at or above market level. Most workers report that cash incentives, stock options, ESOP stock, and ESPP participation motivate them to work harder. The interaction of the effects of shared capitalism with other corporate policies suggests that the various shared capitalist and other policies may operate through a latent variable, "corporate culture".

Michael Kortt and I have a new paper out, looking at the relationship between body size and wages. Here’s the abstract (click on the title for the full paper):

Does Size Matter in Australia?
Michael Kortt & Leigh
We estimate the relationship between hourly wages and two aspects of body size: height and body mass index (BMI). We observe a height premium, with an additional 10 centimetres of height being associated with a 3 per cent increase in hourly wages for men. However, workers with higher BMI scores do not seem to earn lower wages. These results are largely unaffected by controlling for physical health, or (in the case of BMI) instrumenting with the BMI of biological family members. A survey of previous instrumental variables studies shows little indication of systematic biases, suggesting that OLS may provide a reasonable estimate of the causal impact of BMI on wages.

We began the project with a primary interest in whether overweight people were paid less, but eventually realised that the most interesting thing in the data is the relationship between height and wages (at mean earnings, 10cm of height is associated with a $1900 annual wage rise for blokes).

The study is now forthcoming in the Economic Record. This was one of those experiences where the refereeing process led to a much better paper, as we to-ed and fro-ed with the referees and editor Paul Miller over the right specification.