Two-child China, and population ageing myths

China abandoned its one-child policy yesterday. Just about everything I’ve read since explains that this policy shift is a result of fears about dependency ratios; the ratio of the number of non-working age people in the population (children and the elderly) to the number of working age people. As shown in the chart below, China, like most countries, is seeing the start of an uptick in this ratio due to an ageing population.

But the simple fact is that increasing fertility rates isn’t a solution to this problem.

The reason population growth doesn’t solve this problem is that a growing population relies on

1. more children, and hence a higher youth dependency ratio, or
2. more immigrants, who both reproduce (more children) and become elderly themselves. 

The only way population growth can ‘solve’ the age dependency problem is if the growth rate itself continues to grow in a grand human Ponzi scheme.

To make this point clear I have poached the data from a great study way back in 1999 by Peter McDonald and Rebecca Kippen. They simulate a number of Australian population scenarios that represent some of the political views at the time ranging from Harry Recher’s view of a one-child policy coupled with zero immigration, to Tim Flannery’s view that a sustainable long-term population target is 12 million, to Jeff Kennett’s view that immigration should be ratcheted up as far as necessary to maintain a constant dependency ratio.

I show in the graph below the dependency ratio[1] based on the various population projections in their simulations (final populations in 2100 are in brackets).

A few things should be noted.

First, the lowest population projection, the Recher model, gets Australia’s population to 5 million by the end of the century and reaches a peak dependency ratio (DR) of about 2.2. The highest population projection, the Kennett immigration solution, reaches a population of 929.5 million (yes, a billion) in 2100, relying on a population growth rate of over 4% to keep the DR at its 1998 level of about 0.7.

In between these two extremes we have population paths that lead to populations between 12 and 50 million by the end of the century, all of which result in a DR between 1 and 1.5 by this measure.

But here’s the thing. That 0.5 difference in the DR between the radically high and low population projections, can be totally offset by changing the retirement age by just two years - shifting the population at age 65 and 66 from dependent to working age.

At the moment the Australia pension age is shifting two years - from age 65 to 67. If social norms of employment change to accompany this, any ageing problem is already solved.

In short, what seem like insurmountable demographic shifts are actually relatively slow and minor changes in economic terms. Not only does a declining youth dependency ratio offset much of the increase in the age-dependency ratio, but from the perspective of the economy as a whole the potential costs of ageing are minor compared the economic and environmental costs associated with rapid population growth necessary to suppress this ratio.

[1] In these scenarios the dependency ratio is weighted so that a child accounts for 3/4 of a person, and a retired older person (above age 60) accounts for 5/4 of a person.

Queensland will ignore better planning

I wrote a submission during the consultation on reforms to the Queensland planning system. As you are probably aware, my research in this area focusses mostly on teasing out statistically the amount of favouritism happening in high value rezoning decisions.

My submission also focuses on the scope within the proposed Planning Bill for continued favouritism. But I also raise the point that we should enshrine at the highest level that governments of all levels, from Councils upwards, be able to capture the land value created by their planning decisions. As it stands the Bill suggests the opposite should be the case - that Councils are liable for compensation should they downgrade the value of land uses at a location (subject to the land being currently used for that purpose).

In no other area of government do we give away property rights for free, so often. It's a multi-billion dollar annual ritual of gift-giving from the public to politicly-connected landowners.

If you want to listen to a terrific podcast covering the types of mechanisms available to recover value gains from government policy I recommend last week’s Renegade Economist episode, which is the source of the below image as well.

You can download my submission here.

Explaining everything explains nothing: Economics

The below comic probably hits a little close to home for most economists. Poking fun of economists’ naive attachment to their particular brand of rationality, and it’s immense body of hidden assumptions, usually gains responses that are merely signals of tribal loyalties and ignore the substance of the critique.

My colleague Vera te Velde made an improvement on the comic which is also included below, and my reading is that she wants to gain loyalty from the tribe more than defend rationality assumptions in economic models.

While it is certainly true that her improvement is consistent with core economic theories, it really highlights in my mind that these theories are essentially vacuous if they can explain anything and everything imaginable.

In response to the ability of other economists to fit everything within their model (meaning nothing can be excluded), simply because of creatively reversing out a set of preferences that explain the observed behaviour (or as Vera concludes De gustibus non eat disputandum), I wrote

There was simply no phenomena he could not explain with his beloved utility theory. But if the theory explains everything imaginable, then it predicts nothing. I resolved that the theory as it stands, in the revealed preference form, was not falsifiable, though he didn’t seem to understand why that would matter.  

Sure, humans often make calculated decisions, but the more I learn about the nexus between individual behaviour and how we behave in groups, the more I see very little value in rational-individualist views of economic systems that see all behaviour arising from God-given personal tastes. Without acknowledging the necessity of group-coordination mechanisms intrinsic in our behaviour, we are missing the main story.

How to analyse housing markets

Housing costs are typically 30% of household income, while about 43% of household savings are tied up in the value of owner-occupied dwellings. There is really no more important market for the general public to understand when it comes to their cost of living and their ability to save for the future.

But simply talking about the housing market as if it is some monolithic beast will lead you to the error of conflating three distinct markets that must be considered independently to truly understand what is happening. These markets are

1. The land/property asset market
2. The housing service market (annual occupancy from rent or ownership)
3. The residential construction market

When you buy a home on the second-hand market (rather than build yourself), you are actually buying a bundled good which includes a land asset along with a durable housing product that lasts the life of the building. A close analogy would be buying a car bundled with an equity share in the vehicle manufacturer—you get the vehicle for its useful life and the equity asset in perpetuity.

So when we talk of high demand for housing, home prices increasing, and housing bubbles, we must be clear about whether we are 1) talking about the market for the land asset component of the bundled housing good, or 2) referring to the housing service market for occupying homes. Conflating these two markets is the most common error in housing market analysis and leads to conclusions that make little sense.

For example, take the frequent comments about the effect of population growth on home prices. To me, it is utterly confusing. If we are talking about the land asset market, the question then arises about why we don’t talk about the population effects on equity and debt markets, derivatives markets, and other asset classes that could equally see effects. Why would "new" people be willing to pay more for the same asset?

You can see from the graph below that population effects don’t seem to be a major driver of land asset price growth. Areas with a 10-15% population declines have still seen 70% growth in home prices.

Like other asset markets, the reason land prices increase has a lot to do with the reduction of interest rates in the past 20 years. Asset prices are just the capitalised value of future claims on incomes, so a lower interest rate increases that asset value compared to the value of that future income flow. This means that comparing prices of the bundle of house and land asset to incomes makes no sense at all. It would make just as much sense to compare the price of an equity share in Woolworths bundled with a kilo of bananas as a way to measure food inflation. Why not measure the food itself?

Luckily, we do have a market for housing as a produced good that we consume on an annual basis quite apart from the land asset; the rental market. If we measure how much of our incomes we spend on rent, and the quality of the homes we reside in (in terms of area per person), we can apply the supply and demand model to the market. If there really is something going on with population and housing production, it must be observable in the rental market. Looking at the chart below we can see that the rent-to-income ratio declined all the way through the land price boom of the early 2000s. So too did the occupancy rate (fewer people per home) indicating that in Australia more new homes were built than needed to house the new people to the same standard.

So sure, use your supply and demand analysis on the market for produced durable housing goods, but remember that home prices are not the price in that market. Rents are the price in the housing market, while home prices mostly reflect asset prices of the land market.

Lastly, we can look at the construction market, which is driven by trends in other markets, including speculation on land markets. Here the supply and demand approach also works, as periods of high demand for new construction result in increasing construction prices (as demand shift to the right against a resource-constrained upward-sloping supply curve for construction services). But again, the construction market and construction prices are not the main contributor to growth in home prices. In fact, higher construction costs will decrease the value of the land asset, as they provide an additional cost to capturing future income flows.

The situation now in Australia is that asset market dynamics, including lower interest rates, international buying by investors whose return is more than just financial (hence will buy with a lower yield), and simple cyclical timing of investments, are driving up land prices in some capital cities. In some areas, when this asset buying occurs in new homes it also increases demand for construction, pushing up prices in that market as well. But in the housing service (i.e. rental) market, the additional new home construction is suppressing rents.

This is the way to analyse housing markets. Don’t be drawn into the monolithic view by conflating behaviour in these distinct markets.

Doing the housing supply maths

Laurence Murphy is a top property economist at the University of Auckland. I met him last night after a presentation in Sydney where he took on the myth that planning constraints are a major determinant of current home prices in Australia and New Zealand.

He said it is very easy to demonstrate mathematically how little impact even a large increase in the rate of supply would have on prices. But when he shows this analysis to government officials, planners, and engineers who have bought into the supply-side narrative their response is often

“I see your calculations. I follow the logic. But I don’t believe it!”

So I wanted to try the ‘basic supply-side maths’ for myself on the blog to see what sort of effects radical changes to the rate of new housing supply could have, and see if I generate some of the same responses.

Here’s how the maths work. I take the number of new dwelling completions from the ABS for the past 20 years, which is shown in quarterly figures in the blue line of the chart below. Since 1995 new housing supply has been 146,546 dwellings per year on average, which is about a 2% increase in the stock annually, though this moves with the business cycle.

I then add 10% to this number every year to generate a counterfactual world where supply has been much higher over a sustained two-decade period (green line). Then I add 20% just to take an extreme scenario (yellow line). Note that in this exercise I don’t ‘elastify’ supply, which would have higher construction rates in boom periods, and lower construction in a slump. When I run the numbers for a more elastic supply that responds more to both booms and slumps I get fewer homes built compared to what actually happened! This is because when the completion rate falls, it falls faster, offsetting all of the gains from the previous boom. I show a 'twice as elastic' scenario in the next graph in red, which actually results in 8,000 fewer dwellings built in the past 20 years. ‘Elastifying’ supply can’t really be what is desired by those advocating for supply-side reforms. 

Any supply-side housing initiative should simply aim to get more homes built, year in, year out. This is what I capture in my counterfactual scenarios of 10% and 20% higher construction over two decades.

So here is the question. How many more houses would there be now in these counterfactual worlds? And what would the price impact be?

Well, if we had built 10% more new home each year for the past 20 years Australia would have around 300,000 more homes. At a 20% higher rate of completions that's 600,000 more. Sounds terrific! That must have a massive impact on prices.

Well. No.

You see Australia’s current housing stock is somewhere around  9.3 million homes. Around 8.8 million occupied, and many second homes, holiday homes, and so forth that are traditionally about 8-10% of the housing stock. These additional homes in my 20-year supercharged supply scenarios represent just a 3.2% and 6.4% increase in total stock respectively.

The price impact of a 3% increase in supply is a 3% reduction if demand elasticity is unity. That’s it. The price reduction could be less if there are countervailing income effects that lead to outbidding for superior locations.  So twenty years of supercharged supply provides somewhere between 0% and 3% lower prices, which suggests to me that focusing on the supply side is close to a waste of time. In the 20% higher housing completions scenario the effect is somewhere between zero and 6%. About the same as two and a half years of rental price growth.

To put it another way, after 20 years of a 10% higher rate of new supply, rents today would be the same as they were in early 2014.

We can alternatively look at the raw measure of the gains to the amount of floor space per person. Taking the average floor size of homes, which is about 180sqm, and adding 3%, and assigning it to the average of 2.6 occupants, to get an additional 2sqm of floor space per person.

Or we can think of it in terms of occupancy rates — the number of people per dwelling — which would be 2.51 instead of 2.6 with the same size homes under the 10% higher supply scenario.

That’s all you get for 20 years worth of sustained housing supply stimulus. And you get none of that simply from more elastic supply only.

The point is that current massive price increases, in the order of 17% per year in Sydney and Melbourne, simply cannot be explained by anything like unresponsive supply. Not only that, any supply-side effect on prices takes many decades to have any effect, and only enters the price equation via effects on rents.

If we want cheaper housing we need to reform legal structures to shift bargaining power to tenants from landlords, curb speculation through financial controls (and keep stamp duties!), and stop rewarding political parties who promise housing supply as any sort of solution to current prices.

Unfortunately, very few people actually want housing to become cheaper. Around 70% of households are homeowners, around 30% are property investors who come from the wealthier part of society, while most politicians also have a huge share of their wealth tied up in residential property. It suits all of these interests to point the finger at supply because they know it sounds attractive in a naive economic way, but won’t actually reduce the value of their housing portfolios.

As Professor Murphy explained, the consensus around new housing supply as a solution to housing affordability problems is a political construct. This unfortunate political reality is best summarised in this tweet. 

  

Politician: I'm want a new housing affordability policy Expert: So u want home prices to come down? Politician: Hell no! #Australia

— Cameron Murray (@Rumplestatskin) September 9, 2015

Dear reader I hope you see my calculations, follow the logic and believe it!

So, about the inefficiency of stamp duties…

Australia’s economic commentariat is now almost unanimously on board with the idea that stamp duties on property transactions are immensely inefficient and should be abolished in favour of land taxes.

I’ve long held the view that land taxes are the best form of taxation. But the idea that stamp duties are exceptionally bad is not clear cut. Key reference points for this belief are the modelling exercises of economists estimating the welfare losses from these taxes.

The main problem, however, is that there are no transactions in the equilibrium economic models they use, so there is no way to model a transaction tax such as stamp duty. Equilibrium models are ‘pre-solved’ by the Walrasian auctioneer to determine the distribution of goods to a single representative agent.

Here’s what the Australian Treasury had to say when they tried to model the welfare effects of stamp duties.

It is inherently difficult to capture this type of capital transaction tax in a model with a single representative agent. The approach adopted here treats real estate services as an investment good which improves the productivity of the firms, including the housing sector. One way of thinking about this is that real estate agents play a valuable role in finding producers that value the capital the most. Therefore a potential owner will be willing to pay a real estate fee equal to the profit they will enjoy over the previous owner. Within this setting the conveyance duty is treated as a tax on the value of investment and subsequent productivity gains facilitated by the transfer of land and structures.

Translated it reads “our model can’t capture transaction taxes so we’ll just assume the tax is something else to fit it into the model we do have.”

The best micro-level analysis comes from Davidoff and Leigh, who find that the main impact of higher stamp duties is to reduce the frequency of home sales, and of those home sales, some will be from people relocating. In addition, stamp duties are fully incident on the landowner, meaning that they cannot be considered a tax on investment as they are in the Treasury model, since a higher stamp duty lowers property prices by an equal amount. It doesn't add anything at all to the cost of property.

It is not clear that the welfare effect of reduced home sales is negative if some (or many) of those sales are merely fuelling speculation in the housing market. The basic result of all transaction taxes in asset markets hold-- if some of the transactions are simply speculative churn then there can be large positive welfare effects from reducing turnover through transaction taxes. 

So I urge caution about calls to cut stamp duties, even if those calls are accompanied by the proviso that such a change must be accompanied by higher land taxes, and especially if those provisos could likely to be ignored.

Nanny state submission

Australia's new libertarian Senator David Leyonhjelm has called for a Senate Inquiry into Australia's creeping 'nanny state' regulations of individual behaviour. The conflicted Senator, whose main claim to fame so far is to agitate for increased regulations on wind farms despite his apparent principles of freedom, is one of those characters who at least shakes up the dreary world of politics. By coincidence, I do often agree with him on personal freedoms, though on economic freedoms and issues about the distribution of wealth and social support, we disagree quite starkly. The Inquiry is, however, a useful catalyst for considering the evidence of individual-level harm-minimising regulations.

My submission is reproduced below and available in full here.

Background
This “nanny state” inquiry is a timely chance to reconsider the relationship between personal choice and legislated responsibilities, and to consider the evidence that exists of the effectiveness nanny state policies in terms of their intended social impacts.

The Terms of Reference for the Inquiry are:

• the sale and use of tobacco, tobacco products, nicotine products, and e-cigarettes, including any impact on the health, enjoyment and finances of users and non-users; 
• the sale and service of alcohol, including any impact on crime and the health, enjoyment and finances of drinkers and non-drinkers; 
• the sale and use of marijuana and associated products, including any impact on the health, enjoyment and finances of users and non-users; 
• bicycle helmet laws, including any impact on the health, enjoyment and finances of cyclists and non-cyclists; 
• the classification of publications, films and computer games; and 
• any other measures introduced to restrict personal choice 'for the individual‘s own good’. 

I respond to each in turn by taking a practical approach informed by research in these areas. An overarching message is this. It should not be okay to ‘do something’ about a social issue without a rigorous assessment of whether that ‘something’ will even address the issue at hand. Many nanny state regulations are a knee-jerk political response and not policy made with clear assessable objectives.

A second message is this. Healthier citizens need not lead to lower health care costs in general as any disease or injury prevention simply allows another disease to cause that person’s death, and it will also have associated health care and ‘end of life’ care costs.

The research is quite clear that this is the case, particularly for smokers. The following academic results are typical (my emphasis).

Health care costs for smokers at a given age are as much as 40 percent higher than those for nonsmokers, but in a population in which no one smoked the costs would be 7 percent higher among men and 4 percent higher among women than the costs in the current mixed population of smokers and nonsmokers. If all smokers quit, health care costs would be lower at first, but after 15 years they would become higher than at present. In the long term, complete smoking cessation would produce a net increase in health care costs, but it could still be seen as economically favorable under reasonable assumptions of discount rate and evaluation period.

And from here

Until age 56, annual health expenditure was highest for obese people. At older ages, smokers incurred higher costs. Because of differences in life expectancy, however, lifetime health expenditure was highest among healthy-living people and lowest for smokers. Obese individuals held an intermediate position.

Therefore when making policy decisions in the interests of improving individual health, an informed government should not naively justify such decisions on the grounds of reducing the resource burden of public health care, as this argument rarely holds. Decisions must be made on other grounds, of which there are many legitimate ones, such as externalities (in the case of passive smoking in some public areas), information failures, market or political power of interest groups.

Underlying this inquiry is also a question as to the current Australia legal situation in terms of duty of care. Take as an example children’s playgrounds in public parks. Surely a part of the trend towards excessive padding and safety is the result of legal pressures and past legal cases against “negligent” councils. The same happens with cracked footpaths (see this example, and there are many others), and other personal injuries that seem to overstep the bounds of a common-sense duty of care even on private property (see this example). I believe a key part of the process of removing ineffective and costly nanny state regulation requires looking abroad, perhaps to Europe, at how the legal interpretations of duty of care are quite different and allow governments the legal comfort to go without nanny-state regulations.

Tobacco choice
Legislation restricting tobacco sales, purchasing, and smoking location has had a large impact on smoking in the past two decades. As the below graph from the Australian Institute of Health and Welfare shows, smoking is declining in the general population in response to a combination of policy changes intended to have this effect. Now the rise of vaping as an alternative nicotine indulgence has attracted some attention as its growth in recent years is at odds with the continued long-run decline in tobacco smoking in traditional forms. 

 
Questions about tobacco choice must centre on externalities of consumption, and information failures. Is smoking impinging on the freedom of others to enjoy a smoke-free environment, and are smokers fully informed about the products they are consuming?

On the first question, it seems clear that previously introduced limitations on smoking locations have addressed the majority of externalities associated with tobacco consumption. On the second, one could argue that the public awareness campaigns of the past decades have addressed this issue as well, and that plain packaging rules and other changes have little claim to be further addressing information failures, though there is a very light argument that it reduces the power of tobacco brands because of lower community awareness.

The rise of vaping must also be considered. Vaping is specifically designed to minimise externalities from consuming tobacco in public and enclosed spaces, and hence any regulation of vaping should focus on ensuring consumers are fully informed of the product being consumed and its personal health effects.

Alcohol choice
There is no doubt Australia, like many countries, has high levels of alcohol related violence and a binge drinking culture. Australia has some shocking ‘alcohol related violence’ statistics

• 1 in 4 Australians were a victim of alcohol-related verbal abuse 
• 13 percent were made to feel fearful by someone under the influence of alcohol 
• 4.5 percent of Australians aged 14 years or older had been physically abused by someone under the influence of alcohol 

But all the scientific research says that alcohol has absolutely no effect on aggression, and in fact impairs coordination.

One must be clear about what social problem taxes on alcohol and other regulations limiting sale are targeting; the binge drinking that arguable creates externalities on others, or drinking alcohol in general? Clearly it is the rowdy culture and late night violence in cities and suburbs that is a problem.

Yet it is not clear that “sin taxes” on alcohol are an effective way to change the binge drinking culture, and in fact might have the opposite effect. Those who choose to drink alcohol may change their patterns of consumption to only drink to get drunk. Why pay so much for alcohol unless you are going to get drunk?

Anecdotal evidence across countries suggest that countries with binge drinking cultures also have the more expensive alcohol, such as the Scandinavians and the UK. While in Mediterranean countries where wine is part of the dining culture, cheap enough to consume with most meals, the binge drinking culture is less prevalent. In fact the weight of evidence now points to regular small quantities of alcohol being beneficial to lifetime health.

So what sort of policies would reduce our violent binge drinking culture? I have a radical proposal.

• Remove taxes on alcohol (revenues can be made up with land taxes) 
• Reframe the public alcohol messages. 
• Reduce the drinking age to 16 
• Allow alcohol to be sold in supermarkets in States where it is not 
• Remove liquor licensing rules and simply retain responsible serving of alcohol requirements. 

Essentially such changes would make alcohol boring and integrate it into everyday life.

Public health messages might have a grandma drinking Bundy Rum diluted with cold water after dinner, who then falls asleep on the couch. Or we could do a complete reversal and really drill home the point that rowdy drunks are puppets of their social environment and that they can’t blame alcohol. If you are a tool when you are drunk, you are a tool. Embarrass them into less binge drinking.

As anthropologist Kate Fox explains

I would like to see a complete change of focus, with all alcohol-education and awareness campaigns designed specifically to challenge these beliefs – to get across the message that a) alcohol does not cause disinhibition (aggressive, sexual or otherwise) and that b) even when you are drunk, you are in control of and have total responsibility for your actions and behaviour.

Yet at the moment we have alcohol messages that seem to reinforce the message that alcohol is an excuse for disruptive behaviour, with phrases such as “alcohol is responsible for..”. Actually, no. Would you seriously say “tea is responsible for…”. 

As I have discussed before, culture is often a good explanation of social and economic phenomena. The more we understand culture, and get over our simplistic ‘Pigouvian taxes can fix everything’ mentality, the more we can strategically intervene in highly effective ways to change behaviours that are having negative effects on others.

Marijuana choice
The same arguments discussed above in relation to tobacco smoking and alcohol apply to marijuana. It is mostly through historical happenstance that marijuana consumption is fully prohibited while tobacco and alcohol is not, and certainly prohibition of various types of drugs have a complex social history.

The main comment is that modern experiments with legalisation of marijuana have showed that there is little social disruption to such changes, and that legal and police resource devoted to the current illicit marijuana industry can be much better employed elsewhere.

Bicycle helmet choice
Australia is globally unique in our laws about compulsory bicycle helmet for all riders. As discussed in the background section of this submission, the argument that injured cyclists will be cared for in public hospitals, and as such create externalities on other through the costs of public health care, is rubbish.

Moreover, even if one believed this argument it would also justify helmet wearing for drivers and pedestrians, who on average account for the overwhelming majority of head injury hospitalisations.

As a general observation the helmet laws has been a knee jerk policy without a clear assessable objective, and has for nearly 30 years been an excuse to ignore investing in urban cycling infrastructure because ‘something’ has already been done for cyclists to keep them safe.

Again, the overwhelming research findings are that helmet laws reduce cycling, make cycling less safe, and decrease health outcomes for those who opt out of cycling. Being a world outlier in this area should be enough of a signal that this law is not achieving any particular goal of reducing externalities or improving information failures for cyclists, and if anything does the opposite by making cycling appear more dangerous that what the statistic show.

Media classifications
Unlike most of the items int he ToR, media classification do serve to address an information failure, in media and games, where viewers are unable to judge the content until after they have experienced it. The simplest way to view media classification is as a type of labelling, similar to that in the food and groceries, which allows customers to easily access additional information about the product.

In an ideal world media classifications would be simple and their design would imply self-evident feature of the media content in terms of violence, sexual content, language and themes. The main use of these classification is for parents of children who are taking responsibility for their child’s exposure to particular types of media, and hence for these parents some form of classification tools appears to address a possible information failure.

The confused economic orthodoxy

Last year I presented the idea that perhaps a firm objective function of maximising their rate of return on all costs is more consistent with the stylised facts about firm cost curves.

I want to document here two things. First, the two mutually exclusive responses from editors and referees during the reviewing process, which to me reveals the general ignorance of what the core concepts in economics really are (opportunity cost anyone?).

Second I want to spend a moment showing the incoherent ways profit-maximising is used in economics, and reiterate Joan Robinson’s critique of profit-maximisation as it is still highly relevant.

Part 1: Challenging the scriptures
The basic idea of my alternative objective function is that maximising the absolute value of something is universally a stupid thing to do. We need a denominator in a world where what matters at an individual or firm level is relative performance.

I’ve had both the following responses. First is the more common response that the paper is wrong because it doesn’t look at profit maximising firms. Basically, this response involves re-explaining the standard result of profit-maximisation. To borrow Steve Keen’s favourite analogy, we are like Copernicus explaining what a model of the Earth revolving around the Sun predicts, and the response is to explain the predictions of the Ptolemaic orthodox model where the Sun revolves around the Earth. The comments on my first blog post about the paper were mostly along this line.

The second response from editors and reviewers is the opposite. We’ve also been told that return-seeking is natural and implied in the standard model of profit-maximisation.

Your paper argues that firms do not maximize instantaneous profit but instead choose to allocate resources in a way that maximizes return on investment. I don't think that this assumption would surprise or bother anybody.

Actually, yes, it surprises and bothers all your economics colleagues. Maybe you should sit down together and interrogate your own models with some objective clarity and see what they really say.

Even if you dismiss this bizarre series of responses as the outcome of time-poor editors looking for excuses to reject papers they don’t like the look of, you’ve just revealed an acceptance of the non-scientific nature of economics and the lack of openness to anything outside the accepted scriptures (and yes, this is a general social science problem).

Part 2: Sticking with inconsistent beliefs
This is my main problem with economics. Despite a long history of critiques of the core models from inside the discipline, including the impossibility of a representative agent (and it’s full information), the conflation of uncertainty with risk, the Walrasian auctioneer, the impossibility of aggregating capital quantities, and many others, somehow the core survives.

So let me add to this long history of critiques with another of my own.

Consider the short-run profit maximising model, where profits are revenues minus costs. By definition the short-run has a fixed factor of production, usually called capital, which can be any arbitrary set of inputs. What that implies is that the short run profit maximising output actually is more generally represented as

profit = (revenue - costs) / fixed capital amount

Magically we have an implied denominator, which we might consider sunk costs. But then we have another different set of costs in the numerator, the variable costs. Exactly how is this distinction between types of costs made in practice? More importantly, where do the funds come from to pay these variable costs?

Consider the standard short-run price-taking model in equilibrium. Demand then increases. Increasing output requires the imposition of greater costs for each additional unit (being on the upward-sloping part of the ATC), the firm must conjure these costs from somewhere. If they require a new investor (or the same investors to reinvest earnings), they are diluting the rate of return on all the other investors.

As I have explained before, no current investor would allow the rate of return on their share of the firm to be diminished by adding additional investors. Essentially the core short-run profit-maximising model is one of maximising profits per capital owner.

But then we have a long-run profit maximising model which typically looks like this

profit = quantity * price - (labour units * labour unit cost + capital units * capital unit cost)

The denominator has disappeared. All of a sudden firms don’t care how much it costs to make a profit. If there is a choice between spending $100 to make $40 profit, and spending $200 to make $41 profit, you choose the latter as a profit-maximiser.

But as a return-seeker you first take the $100 investment. You don’t ignore a 40% return because a 20.5% return is available elsewhere. Never.

There is much more to this story, particularly around the ability to leverage. But the biggest story is about how value is gained from high return investments. If I can get my 40% return on costs, I can later sell that firm based on the discounted value of net cash flows. If that discount rate is, say, 10%, then my $100 investment gains $27 in value immediately. I can then sell my firm for $127.

In any case, the point here is that profit-maximisation is, in the words of Joan Robinson, meta-physical doctrine. The empirical record is against it, yet it persists as a signal of membership to the economics tribe. And what is worse, it seems that very few economists at the top of the discipline are clear about the crucial and often hidden underlying assumptions of their models, and continue to teach a fairy-tale view of the core models.