Monday, 29 September 2008

Is Sub-Saharan Africa threatened by the world financial turmoil?

There have been concerns raised that the world's poor could suffer as a result of the credit problems which are tearing through the US and European financial centres. There are indications that contagion has spread to parts of Sub-Saharan Africa, with one of the major South African insurers suffering large losses and share price falls in recent days. One could also see a scenario where European and US aggregate demand collapses in response to the credit contraction and they stop buying African goods and erect higher trade barriers.

The pessimistic view could see an aggregate demand decline in the West lead to a downturn in China and the rapidly growing developing economies, whose growth is supported by high investment rates but correspondingly low levels of consumption. The decline of the whole world economy would of course badly affect Africa's recent brisk growth. The imbalances between the high consumption West and the high investing developing countries are perhaps the most serious threat facing the world economy today, and the period between the time these developing countries catch up with the West and the time they adopt Western consumption levels is likely to be difficult.

A more optimistic viewpoint would observe the multipolar nature of the world's economy, and significantly that the global credit sources and global demand sources are not precisely identified. A financial crisis in a single country, even one as large as the US, does not necessarily precipitate a global crisis of comparable severity.

My view is that the West will suffer most from the current crisis, but the world economy will also slow. A full judgement would be based on a probabilistic analysis of all possible scenarios.

The "suddenly silly" explanations of the credit crunch

I find it difficult to accept the explanations of the current credit crunch which essentially say that bankers in the world's financial centres have suddenly started behaving foolishly, making huge imprudent loans. The argument seems to be that they used to be smart but today they are silly.

It certainly could be the case that people have changed. But the world economy has changed so quickly that it seems likely that systemic or structural changes in the latter are at least among the major contributory factors to the credit crunch.

Procedure for generating macromodels from microfoundations

Macroeconomic models today are often generated from microfoundations, whereby an economy's behaviour is constructed from assumptions about the behaviour of individual consumers, companies, and countries. The approach tends to allow for a fuller inclusion of Keynesian and classical behaviour in the model than approaches which start from macroeconomic behavioural assumptions.

The modelling also is usually a bit more involved and so the published models are fairly simple with assumptions like identical consumers, one company, or two countries. I've been trying to improve my own humble modelling, and think that the following procedure is quite helpful for building models without immediately being overwhelmed by the simultaneity and interactions between the variables. It has its own simplifications built in, but gets the modeller going down the path.

The steps start by specifying a utility function for the demand side of one of the fundamental goods or services in the economy. The utility function should describe how the good and its trade-off payment interact - for example the trade-off between a good and wealth, or between production and labour, or between income and leisure. Simple linear utility functions like U(good) + U(wealth-payment) tend to be analytically amenable. The function is solved to get an equation connecting the two elements. A supply equation is then specified, which may be monopolistic for simplicity so that the supplier can choose the point on the demand curve, or may be competitive to get an upward slanting supply curve. The two equations for supply and demand may be solved explicitly to get the amount of the good purchased or solved implicitly or graphically. This is a solved model for the good/trade-off pairing.

Either the supply or demand curves may then be expanded to include another good/trade-off pairing, and the new model solved in the same way. The model can keep on expanding as required.

I have only applied this approach to a basic model (one good, one company, one consumer, one bank) to get the money and good demand in an inflationary environment, but it is really easy to use compared to everything else I have tried and looks vaguely like the models of the leading figures in the field. I haven't tried closing the model with simultaneous equations using labour demand.

A real scoop would be a full growth model built from microfoundations, as most major microfounded macromodels do not seem to be aimed at analysis of economic growth. I am not sure if it would lead to many more insights than basic growth models, however.

Thursday, 25 September 2008

The effects of the US bail-out plan

The US government is planning to spend US$700 billion on purchasing bad debts from its banks, so that the banks will have more money to lend to each other and consumers. The idea is to stop many banks becoming bankrupt and prevent a severe recession. There is much debate in the US as to whether the plan is a good idea, and it might not be approved by other parts of government which control the finance.

I suggested in Monday's post that the credit problems were likely to have been caused by factors linked to rising debt in the United States, and by factors linked to reductions in the availability of international lending to the United States. The former factors are common in economic recessions, and are often dealt with by financial packages which, if they do not prevent recessions, at least make them less severe.

The latter factors arise from features of the world economy such as the cost of oil and the size of financial surpluses retained by the US's trading partners. A financial stimulus package is unlikely to rectify them except in the short term, and will lead to increased transfer of money out of the US. The package itself is reported to be funded exclusively by debt. The problems are likely to return at a future date.

It is difficult to judge how much the problem is domestic and how much international, and it is understandable that the part of the US government responsible for financial matters wants to look carefully at the colossal sums of money to be paid to banks.

Productivity growth under different economic systems

Many communist countries had high reported investment rates and high levels of human capital, but lower levels of incomes per person than capitalist countries. Some major economic growth models are evasive about the reasons for the difference, as they describe output and growth in terms of productivity, capital, labour, and human capital. Assuming that productivity levels could equalise across countries, communist country incomes should have been higher, not lower.

Productivity levels evidently did not equalize. Sometimes it was said (I can't remember where) that communism was good at large capital projects like steel production, but less good at innovative projects. I am cautious about accepting this as the single explanation for the income differences, and won't accept it at all without evidence. But there is some logic as to why a centrally directed state would not be great at innovation. In recent years, higher growth from technology projects has happened in countries with stock exchanges so that venture capitalists can realise their initial investments, and flexible markets so that technology start-up companies can form and fold without excessive cost. Neither of these features characterise state-controlled markets.

I think that any theory comparing economic systems should give great emphasis to examination of their relative effects on productivity and its growth.

How important is knowledge for capitalism?

Large-scale capitalist economic growth has only happened for the last few hundred years, and it is not obvious why it started in the 18th Century rather than at any point in the 100,000 year (or whatever) history of humans. By capitalism, I mean either market capitalism, state capitalism, or any of the other varieties of production based on physical input accumulation and subsequent exchange.

People have exchanged goods throughout recorded history, and to get to a capitalist system people would only have to save some of the goods they produce with the purpose of using them for making future goods. It is such an easy and obvious thing to do that it seems most likely that not only humans would have done it throughout their history, but also other animals. Some animals store food during the summer so that they can eat it during the winter, and presumably a proportion of them share the food with their family or pack. It is local capitalism, with the accumulation of value occurring because the animals survive and can perform the same task the following year. (The depreciation of the capital is probably close to 100 percent per year, so some economists would classify the saving as delayed consumption, but I think of consumption and investment as a continuum.)

The output of production is determined by the productivity of inputs, including capital, times the amount of those inputs. If productivity is low, then saving large amounts of capital will not be rewarded well.

Productivity is determined to a large degree by knowledge, particularly scientific in character. So as human knowledge grows, the productivity of output grows and the likelihood of investment being a worthwhile activity rises. The burst of modern scientific knowledge from the 17th Century onwards probably was key in the rapid growth of capitalism subsequently.

To return to the animal example, animals getting smart might raise the productivity of their work. For example, if they hide food near their winter lodgings or make it easy for themselves to find their food, they will expend less energy in finding it during the winter and so have to consume less. Any spare food left unconsumed after the winter may seed and create more spare food for the following winter, and so on.

A fully fledged market system for animals with banks, wage employment, unionisation, unemployment, money, and inflation seems unlikely to emerge, but it's a nice thought...

Monday, 22 September 2008

Is there a credit crunch?

There is a credit crunch where banks and consumers find it difficult or impossible to get loans, at least in the United States. The existence of the credit crunch is actually quite puzzling. A few years ago, there was said to be a global credit glut, the newly industrialising countries have large amounts of capital from selling their goods abroad, there has been far more money transferred to oil producing countries than at any time in the past which should be available for investment internationally, and there has been continued growth in spending in the UK Premiership by multimillionaires which is a sure if crude indicator of the existence of spare capital.

So what's going on? Here are a few likely explanations.

The first is that past debt in the US economy has become so large that banks cannot lend much more without compromising their reserve ratios.

The second is that the borrowers have reached the limit to which borrowing boosts their disposable income, so that economic growth starts to decline as they pay back debt, leading to an economic downturn in which their ability to pay back debt declines in a cycle.

The third is that declines in the value of the US dollar means that international capital is less willing to convert into the currency as continuous decline means lower returns.

The fourth is that the new global distribution of wealth has not been accompanied by a corresponding redistribution in the ability to make loans, so that the newly rich are less able to lend their money efficiently in the US.

African Union problems in Somalia

There has been fighting between Somali insurgents and African Union peacekeepers in Mogadishu in recent days. There are reports that the AU bases came under attack in simultaneous raids.

The United States peacekeepers in Somalia in the early 1990s had well-known difficulties in the country, and their lack of success may have been a contributory factor to their decision to stay out of Rwanda during the massacres of 1994. If the US had known that their problems were not necessarily because the West could not intervene successfully in Africa, and that Africans would encounter the same difficulties, they may have intervened in Rwanda and stopped the bloodshed.

Thursday, 18 September 2008

Procedure for instrument selection

Instruments in estimation methods are variables which are correlated with the explanatory variables but not the error term. Whether or not a proposed instrument set is uncorrelated with the error term is tested using statistics like the Hausman statistic and Sargan statistic. Choosing sets of instruments can be difficult, and sometimes seems to be a brute force and ignorance procedure, where one tries a set, sees if it is accepted on the statistics, and if not tries another, sees if that is accepted, and so on. There are rules for rejecting instruments sets without testing them if they are very likely to be rejected anyway, for example if a variable is known to be influenced by changes in the explained variable, then it is probable that variable should not be used in the instrument set.

Here is a procedure which embeds some more rules for selecting reasonable instrument sets. The procedure is a work in progress - I am still trying to sort out an instrument selection process that is not frustratingly arbitrary - so it may be revised in future, and some of the steps might not work very well. I will explain some of the logic further in future posts, too.

1. Choose a base set.
2. Check the Hausman or Sargan statistics.
3. If the statistics have low probabilities, try removing the variables with low significance. If the probabilities rise, then the low significance may occur because the omitted variables are related to the instruments but should not be in the regressions.
4. If step 3 is not possible because there are no insignificant variables, then try using older lags of the variables in the instrument set. If the probabilities do not rise, the equation specification may contain omitted lags itself, or an incorrect functional form.
5. Try different instrument sets entirely.
6. Repeat from stage 2.

Every unsuccessful loop of the procedure increases the likelihood of misspecification.

Monday, 15 September 2008 downtime

My website is erratic in displaying its externally linked sources, leaving the site looking barren. I will adjust the contents to make it work better. Stay tuned!

SSA in the Millenium Development Goals Report

The Millennium Development Goals Report came out a few days ago. Here is a summary of its statistics concerning Sub-Saharan Africa. Changes are for the last ten to fifteen years.

Around 2/3 of people of working age are employed.
Around 70 percent of people are self- or family- employed.
The number of employed people living below $1 a day fell a little.

The percentage of underweight under five year olds fell a little.
Primary school enrolment increased a great deal.
Under five year old mortality fell moderately from a very high level.
Measles vaccination increased a great deal.
Adolescent fertility fell a little.

Gender (some overlap with children section)
Girls' gap in primary school enrolment behind boys narrowed a little.
Women's participation in non-agricultural wage employment increased a little.
Women's participation in politics increased a great deal from a low level.
Maternal deaths remained at a very high level.
Skilled health personnel attendance at births increased a little.
Antenatal care rose a little.
The gap between a women's wish to delay child rearing and contraceptive use fell a little.
Women represent a slightly higher share of HIV infected people.

Access to HIV antiretrovirals rose moderately from a low level.
Access to insecticide treated mosquito nets rose a great deal from a low level.
Tuberculosis infections rose a great deal from a high level.

Greenhouse gas emissions rose moderately from a low level.
The proportion of land and marine areas protected rose a little.
Use of improved sanitation facilities rose moderately from a low level.
Access to improved drinking water rose moderately.

Internet use rose a little from a low level.

Proof of GMM System and Difference selection of high values in misspecified AR(1) models

Here's the proof that the GMM System and GMM Difference estimators select high values from the range of an autoregressive parameter in an AR(1) model, where the autoregressive parameter is assumed to be constant across groups but isn't. There's an assumption of ergodicity. They are close to a general proof for all GMM estimators with parameter-linear orthogonality conditions, and the proof that the GMM System selects higher values than the Difference estimator should follow from the result that (a/b > c/d implies a/b > (a+c)/(b+d)). But I haven't pushed these results through.

The results are in image form because there are some formulae which don't paste directly.

How to minimise the time taken for revisions of a research paper

Revising research papers after they are written in first draft is time consuming and, for me, tiresome. Here is a procedure which may help to minimise the time taken for revisions, and generally streamline the production process. It is intended for analytical research papers.

Question preparation
1. State a question with evident importance, capable of giving interesting results even if the prime hypothesis is rejected
2. Split the question into sub-questions for examination
3. Perform a literature identification of anyone who has done anything similar
4. Write down the literature’s questions, approach, results, etc.
5. Produce more precise questions and sub-questions in the light of the literature review

Specification preparation
1. Draw up rough testable specifications capable of answering the question and sub-questions
2. Check data availability for being able to answer the questions
3. Produce a theoretical derivation getting roughly the specifications
4. Rewrite the specifications for the question and sub-questions as indicated by the derivations

Data preparation
1. Get the data for the specifications
2. Write down any potential data problems or impacts on the specifications
3. Process the data for exact suitability
4. Summarize the data and store the table somewhere

1. Select appropriate estimation methods
2. Estimate and store results
3. After each estimation, summarize the data used and store the table somewhere
4. Highlight any clear inadequacies in the estimations including data in inappropriate units so as to make the results easy to read – the earlier identification of data problems may help
5. Revise the estimations until all inadequacies are resolved

(For all the following steps the contents should be perfectly presented when first added. The structuring of all the sections should be as normal, eg
Questions / importance / literature review / plan / theory / specification / empirical specification / inputs / outputs / interpretation / conclusion.)
1. Set up the paper with a statement of the correct specifications
2. Add result tables
3. Add the interpretation section – the earlier identification of data problems may help, as may the stored summary data
4. Add the conclusion section
5. Add the inputs section
6. Add the specification section (the non-formula parts)
7. Add the empirical specification section
8. Add the inputs section
9. Add the plan section
10. Add the questions section
11. Add the importance section
12. Add the literature review section and bibliography at the same time

1. Proof read and spell check

Thursday, 11 September 2008

Growth impacts of Australian and UK university education

I reviewed some regressions connecting university student inflows into Australia and the UK with economic growth in the countries sending them. It turned out that on average, Australian education is associated with three times the growth increase as UK education.

Perhaps Australian education is much more economically productive than UK education. But the statistic on its own doesn't say that. Other factors which may influence the relation are whether students return home after they complete their courses, the type of education, institutional factors facilitating the use of education, motivations for taking or providing education, regional origin since Australia attracts more students from high growth Asian countries, and causality since we had to use OLS as the student data was only available for one year.

Motivating new research students

Many students, particularly at Master's level, are highly motivated to produce immediately useful work for their topic of interest. A problem is sometimes that they do not have the technical training to do so quickly, and it can be irritating for them to struggle to match their ambition to their untrained ability at implementation. The often slow pace of academic production and the impression that advancement is more to do with adoption of academic attitudes and norms than reaching the student's goals can be further causes of disillusion.

I think that expressing the rate of student improvement - which can easily outstrip the improvement of world class researchers, simply by virtue of the different starting points - could help to offset the problem for some students. It is entirely feasible that after a one year course a student could produce work with similarities to that of leading researchers, even if actually reaching them may take longer.

There are several difficulties communicating the aims to students. The first is promoting the idea that a Master's course is more about training than new applied research. The second is promoting the idea that initial training will benefit them more and quicker than immediate research. The third is finding a measure of quality which will capture improvements without initially discouraging students through its low level.

Monday, 8 September 2008

How much economic activity happens?

Some things tend to increase the amount of paid work done, such as the wish to make money, while other things tend to decrease it, such as leisure preference. Total economic output balances the two. Can more complicated equations be derived showing how much economic activity happens at any time?

I think a little econophysics might help to answer the question. Econophysics is the application of physical science to economics, and has some attention in the economics literature. Mainstream economics has always borrowed from physics and applied mathematics, but econophysics tries to make very close analogies.

I am thinking about minimisation of energy in a particle's flight when thrown upwards. A particle minimises the amount of energy it takes to move, so that the integral I(kinetic energy - potential energy) is minimised at all times. The principle is equivalent to saying that the particle moves under the influences of forces acting on it (kinetic energy upwards, potential energy downwards), and only on them. The analogy with economic activity is clear - an economy grows (respectively, contracts) only if the effect of the forces on it is positive (respectively, negative). I am not presently smart enough at physics to determine how energy, force, and the minimisation equation are exactly related, and the economics version of the integral minimisation may not be in precisely the same form.

If the economics integral could be established, there could be some snazzy toys waiting. The integral minimisation in physics gives rise to such helpful relations as the conservation of energy, and similar expressions may be available in economics. Answering how much activity occurs at any point in time would be a great result.

Simple growth model including debt

Here's a simple growth model which includes debt.

Suppose the consumers in an economy borrow a net amount D to finance spending. The output in the economy is assumed to rise to meet the increased demand for goods. Thus, output is Y+D, where it would be Y without debt. The increase is thus a factor of 1 + d, where d=D/Y.

The increase may generated by increased capacity usage, if the labour and capital markets are not flexible, or by increased factor accumulation if they are. In the former case, with a growth model of output (Y) = factor productivity (A) * factor terms (F) , the output would change to A*(1+d)*F. In the latter case, the output would be A*F as before. Economies are partially flexible in reality, so the model is Y = A*(1+d)^a*F, where a is a constant.

Taking logs and differencing,

growth in output = a*growth in (1+d) + growth in F

The model allows for debt-funded booms and sharp downturns when the credit has to be repaid. Assuming a personal debt limit of say 200 percent of earnings on average, ten percent interest rates, and debt able to increase by twenty percent per year, then starting from no debt, an economy can expand through debt for a maximum of ten years before the repayments would inevitably lead to a slowdown.

The adjustments in capital and labour would not be instantaneous, so the debt funded growth and contractions would be subject to delay rather than being instantaneous as here, and capacity may not be available in an inflexible economy, so inflation would result rather than expansion. For all of its limitations, the model is not bad for empirical estimations.

What is doing the work in empirical growth models?

Most empirical growth models are not theoretically complicated. For example, one may be based on the assumption that output is

Output = A * Capital ^ a * Labour ^ (1-a)

or, dividing by labour,

Output per person = A * Capital per person ^ a

where A and a are constants. If one takes logs in the equation, then subtracts the same equation in the previous time period, one gets

ln output p.p.(t) - ln output p.p. (t-1) = a*(ln capital p.p. (t) - ln capital p.p. (t-1))

The left hand side is approximately equal to (output(t)- output(t-1))/(output(t)), which can be shown by using the Taylor expansion for ln (1+{output(t)/output(t-1) - 1}). The term is thus approximately equal to the growth in output, and we have a model

growth in output p.p. = a*growth in capital p.p.

The model has ignored many aspects of the economy, such as alternative production functions, differences across countries, aggregate demand, changes across time, other influences on growth, and influences of growth on changes in capital.

Yet the empirical testing of the model has been reasonably successful. One of the reasons is that the empirical testing does much of the clean-up work for the model. For example, if we test

growth in output p.p. =
a*growth in capital p.p. + country specific constant + time specific constant + error

the error will often be robustly estimated, so handling wide fluctuations in the quality of the fit and the direction of the model's bias. The country and time specific constants capture factors which may dwarf the explanatory power of the basic model. The estimation will frequently employ methods to handle endogeneity of variables, which allows for the possible omission of other relations between the variables in the model.

In short, if a growth model is assessed to be an empirical success, it is usually the model and the estimation method which are the successes.

Thursday, 4 September 2008

Endogenous growth through technological innovation

As a further point to make on the last post, the tentative results imply that growth could be sustained indefinitely rather than heading to a steady state, although it would slow through diminishing returns to capital. Indefinitely here means a few decades, since economies could change hugely in the period rendering the model invalid. Pretty short time period for "indefinitely"!

My estimations indicate that having a higher proportion of the world's computers and researchers tends to increase growth, and that other countries cannot obtain, in the short term, the growth benefits associated with their ownership just by transferring technology from abroad. Thus, there seems to be a definite advantage with being a technological pioneer, which may help to explain the ability of economically advantaged countries to sustain their growth over time.

The coefficient on the lagged income term in technological growth models

Estimations of the growth model

income growth per person = constant0
+ constant1*income last period
+ constant2*capital accumulation
+ constant3*education increase
+ constant4*technological transfer from abroad
+ error

typically find constant1 less than zero if constant4 is set to zero before the estimation begins. So as income increases, growth declines.

If technological transfers are allowed and constant4 is estimated rather than set to zero, then my recent estimations have found constant1 to be very small, and may be positive or negative. It would seem that technological transfers account for much of the reason why growth is estimated to be lower in rich countries than in poor countries, when cross-sectional or panel data estimation is used. It also helps to explain why time series for economically leading individual countries often do not show such marked declines in their growth as would be expected from estimations.

The results are sensitive to the estimation method, and so are quite tentative at the moment.

Religious affiliation and women's workforce participation

As a possible partial answer to the question raised in the last post of factors which have influenced increased women's economic participation, the rise in secularisation of society may be one. A paper in a leading economic journal in 2003 ("People's Opium? Religion and Economic Attitudes") found that people who were actively religious or even just raised religiously were more likely than non-religious people to think that:

1. When jobs are scarce, men should have more right to a job than women
2. Women should have children in order to be fulfilled
3. Being a housewife is just as fulfilling as working for pay
4. A university education is more important for a boy than a girl

The authors split the results by religion for questions 1 and 4, and find that Muslims tend to agree most with them, followed by Hindus, then Catholics, and then Protestants. Members of the smaller religions have wide variation in their opinions. There may be some advantage in religious expansion through supporting the views, perhaps through increasing family size. Being an atheist significantly lowers agreement with the statements. Women have obtained more prime ministerial and presidential positions in countries with the large religions as the largest belief systems than in formally atheist countries or countries associated with smaller religions, so there may be some political-economic trade off or internal social tensions at work.

The paper is not available online, but the survey data it is based on is free at There is considerable variation by country, and some of the results can be surprising. The data covers much more than just attitudes to women or religion.

Granger causality between growth and women's education

Here's a little evidence from Burkina Faso on the Granger causality between per capita economic growth and women's education, or to put it another way, whether economic growth happens first or women's education happens first. The examination contributes a little to the question of whether women's rights are to any extent a product of capitalist expansion directly or whether women's rights are the product of social changes generated outside of capitalism, in the sense of not being the result of demands by profit maximising companies. The latter interpretation does not exclude the possibility that the social changes have been enabled by capitalist social structure changes.

Two models are empirically tested. Estimation 1 is

Growth in a country =
+ constant2 * growth in a country some time ago
+ constant3 * women in primary education as a percentage of total people in primary education the same time ago
+ error

and estimation 2 is

Percentage of women in primary education =
+ constant5 * percentage of women in primary education some time ago
+ constant6 * growth in a country the same time ago
+ error

If growth has a positive effect on women's participation in education, then the constant6 will be positive, and conversely if it is negative. If the evidence is weak, then constant6 will be insignificant, that is, estimated with much uncertainty in the results. If women's participation has a positive effect on growth, similar statements apply to constant3.

I focussed on Burkina Faso because it has increased its women's participation in education from 36.9 percent in 1980 to 42.2 percent in 2002, so has some variation in its figures allowing for more precision in estimation. Western countries generally have had constant levels over the same period, and data was not available from the sources used (annual 1980-2002, from the UN and Penn World Tables) over earlier periods. A larger number of countries could have been used, but would have increased the time for data preparation. Burkina Faso also has avoided very severe social and economic dislocation during the period under consideration, which would distort the data.

OLS estimation was used, which is consistent for large amounts of data; we have 22 years worth, so the results should be reasonably accurate.

For estimation 1, constant3 is positive over all time lags. The first significant coefficient comes at time lag 6, when both constant2 and constant3 are significant at ten percent. A delay for the effect of increased female educational participation on growth to be evident would be expected. Thus, per capita growth appears to be positively associated with earlier increased female educational participation in Burkina Faso.

For estimation 2, constant6 varies between positive and negative signs depending on the time lag, and never comes near to significance at ten percent. Thus, economic growth does not seem be associated with future increased female participation in education in Burkina Faso, and increased participation seems likely to have been caused by other reasons. The results suggest that pure economic growth considerations - which may proxy for corporate profitability - have not influenced women's participation to any great extent in the country.

The results are an indication of the degree of influence capitalism exerts in Burkina Faso, and the importance of other social factors in effecting a major change in policy. Burkina Faso is still a pre-capitalist society to a great extent, and it would interesting to see whether the results translate to other countries and different measures of women's equality, and in particular to more capitalist societies. It would be surprising if economic growth seems to exert no influence on women's equality, since capitalist development is clearly a huge influence on society and possibly the principal one. If it is not significant, then the question arises of what social influences have been significant enough to effect apparently large changes in women's social participation over a very brief historical period.

Monday, 1 September 2008

Record reductions in track records

One of my interests is track athletics, and I am fascinated by reductions in world record times over distances. It impresses me most when there are major reductions in the records, since the record holder has not just been fit and naturally gifted, but has had the mental toughness to do something no-one has come near to before, and in doing so moved the whole sport forward.

Wikipedia has lists of world record progressions from this page; in all events beyond 800 metres, African men feature prominently. The women are less prominently featured, which could be for several reasons. The most substantial recent record reductions by African men are the 1.4 second reduction in the 1500 metres in 1998; the 4.5 second reduction in the 3000 in 1996; the 11 second reduction in the 5000 in 1995; and the minute reduction in the half-marathon in 1993. These would all be the equivalent of a reduction of more than 0.05 second over 100 metres. The 5000 metre reduction is the equivalent of 0.14 seconds off the 100 metres time, and is the largest percentage reduction here. Given when it occurred, in a frequently competed event, and the subsequent competition to reduce it further, it is arguably the most impressive revision of a track record in recent years.

Recommendations for a start-up economy's institutions

I'm polishing a research paper at the moment, and don't have too many new results to report. So I thought that it would be a good time to consolidate some earlier results, and produce some recommendations for the economic institutions of a newly established country or newly autonomous region within a country:

1. Technology transfers from rich countries have a huge effect on economic growth. Getting students into foreign countries is often associated with growth, as are some forms of imports of technological goods. Poor countries are probably going to benefit more from transfers of less advanced technologies than of cutting edge ones, so building domestic industries accordingly might be a good idea.

2. A recent paper on growth found that presidents are frequently good for their economies for a decade, but their performance drops off afterwards. A four and a half year term for the government, possibly with limits on presidential or prime ministerial office of two terms, would seem to allow for changes before the performance falls.

3. Oil producing states may wish to create strong competitive meritocracies in promotions to government and senior administrative positions. Output in their economies responds less to educational accumulation than output in non-oil producing economies, so educational achievement is likely to be rewarded relatively poorly in the market.

4. Transparency and education in government are important for avoiding foreign investors gaining excessive returns in a country.

5. In dealing with foreign countries interested in gaining control over a country's resources, it may be possible to play the foreigners off against each to achieve greater benefits.