The more things change, more they remain the same - macroeconomic policy edition

The breakdown of the Philips curve relationship between inflation and unemployment has been among the major casualties of recent macroeconomic tumult. It has led to demands that central banks replace the current New Keynesian (NK) models involving a demand equation, a policy rule and a Phillips curve to calculate interest rates.

Over the past few years, Roger Farmer and co-authors have shown that an alternative, the Farmer Monetary (FM) Model, which replaces the Phillips curve with a new equation, the belief function, outperforms the NK model by a large margin when used to forecast the US data for the period from 1954-2007. He writes,

The belief function captures the idea that psychology, aka animal spirits, drive aggregate demand. It is a fundamental equation with the same methodological status as preferences and technology. To operationalise the belief function, we assumed that people make forecasts of future nominal income growth based on observations of current nominal income growth... Conventional dynamical systems have a stable steady state that acts as an attractor. The economy will converge to that steady state, no matter where it starts. The FM model does not share that property. Although the economy follows a unique path from any initial condition, the FM model has a continuum of possible steady states and which one the economy ends up at depends on initial conditions. The FM model explains the data better than the NK model because the unemployment rate in US data does not return to any single point... 

The unemployment rate, the inflation rate and the interest rate are so persistent in US data that they are better explained as co-integrated random walks than as mean-reverting processes. The FM model captures that fact. The NK model does not. What does it mean for two series to be co-integrated? I have explained that idea elsewhere by offering the metaphor of two drunks walking down the street, tied together with a rope. The drunks can end up anywhere, but they will never end up too far apart. The same is true of the inflation rate, the unemployment rate and the interest rate in the US data... the NK model is wrong and there has been no stable Phillips curve in the data of any country I am aware ever since Phillips wrote his eponymous article in 1958.

If the recent Peterson Institute conference on Rethinking Macroeconomic Policy is any indication, Farmer and Co may have more work to do. As Matthew Klein writes in FT, the conference co-Chair, Olivier Blanchard, reaffirmed his faith in the Phillips Curve,

I have absolutely no doubt that if you keep interest rates very low for long enough the unemployment rate will go to 3.5, then 3, then 2.5, and I promise you at some point that you will have the rate of inflation that you want.

Translation - keep the monetary accommodation on and unemployment rates will keep going down till they stoke off inflationary pressures "at some point"! Coming as it does from someone who was till recently the Chief Economist of IMF, this is a staggering level of obduracy. And he was leading a conference on "Rethinking Macroeconomic Policy"!

Klein decomposes the Blanchard view in terms of four propositions - jobless rate influences wage bargaining; workers bargain over nominal and not real incomes; workers spend extra money on consumer products, driving up prices; and businesses in the aggregate can raise pay or hike prices. The last three, especially the last, stand on tenuous foundations and limited empirical evidence.

Thankfully, the rest of the conference appears to have been more receptive to change. The most useful reminder for macroeconomists came, as usual, from Dani Rodrik,

The ratio of redistribution to efficiency gains is not only very large, it rises to ridiculous heights as the tax/policy distortion that is removed gets smaller.

He shows that redistribution per dollar of aggregate gain (in favour of the well-off or entrenched) increases sharply as the tax and tariff rates get ever smaller.

Jason Furman called for an end to the debate on whether inequality is good or bad for growth and on its impact on the average of incomes, both irrelevant for policy makers. Instead, he proposes more attention on specific policies that increase or decrease inequality and their impact on indicators that reflect more broader social welfare functions than simple averages (like the impact on specific population categories). His suggestion for developed and developing countries,

In advanced economies a lexicographic framework that focuses exclusively on distributional analysis and then only to growth when the distribution of different policies is the same is generally likely to be appropriate under a broad range of social welfare functions. This is because the distributional effects of many policies are orders of magnitudes larger than the growth effects. In developing economies, however, the scope for policy- and institutionally-induced variations in growth rates is much larger and thus the lexicographic approach is unlikely to be as widely appropriate.

Gita Gopinath puts to rest the orthodoxy about the superiority of freely floating exchange rates and argues in favour of managed floats for emerging market (EM) economies. Channeling BIS economists and Helene Rey, who claim the impossibility of monetary policy independence irrespective of the exchange rate regime, once capital flows are allowed, Gopinath points to the recent work of Obstfeld and Co which shows the persistence of an attenuated version of the trilemma. They show that for EM countries the correlation of a bunch of macroeconomic indicators and global investor risk aversion is lowest for those with intermediate exchange rate regimes.

She also points to the work of Falk Brauning and Victoria Ivashina about outsized influence of US monetary policy cycles on EM economies, driven by global banks, as shown by their finding that over a US monetary easing cycle they experience a 32 per cent loan volume increase.

Weekend reading links

1. Fascinating work by Johnny Miller to highlight segregation in cities using birds-eye view photographs taken using drones.

Such photographs have a powerful way of shaking people out of their comfort zones and generating conversations on the issue of widening inequality and its manifestations.

2. On segregation, nice Citylab interview of Macarthur Prize winner Nikole Hannah-Jones about how racial preferences entrench de facto school segregation in the US. This is spot on,

What we see come immediately out of [Brown v. Board], when you can no longer explicitly use race to segregate schools, is a very adaptive strategy that white Americans have. Suddenly, you take up the banner of race-neutral language that you know will produce the same result. So it becomes about “local control”—saying “our tax dollars shouldn’t go to educate other children,” or “we want a small local school system that only serves our community.” Of course, that community is all white.

In a place like New York City, where you have a great deal of segregation, you have a neighborhood school system for elementary school, which means your kid will go to a neighborhood school. And since neighborhoods are highly segregated, that means your kid will likely go to a school that is also segregated. But then once you get to middle and high school, it is a “choice system” where white kids go to screened schools— schools that have these apparently race neutral screens, but where you have to have a portfolio, or where you have to take a test to get in. What remains the same is that white parents are going to get access to the best education in a public system. They’re going to get access to disproportionately white schools, and they will wield an array of tools to do that. So if the neighborhood that those white parents live in is white, they want neighborhood schools. If the neighborhood school that those parents are near is black, then they want choice. So people will say they don’t want bussing, if their neighborhood school is white. If the neighborhood school is not white, they’ll bus their kids an hour away to get to a white school.

At some level, the difference between Trump and the liberals are not as glaring as you think. Trump acts and does so with brazenness what most others secretly nurture inside or share across the dinner table.

3. I have blogged earlier about this, but worth repeating this time with Andy Mukherjee's graphic on the critical role of excise duty of petroleum products in India's fiscal consolidation.

The flip-side is that as global economy steams on, the only direction for oil prices may be upwards. This would set in motion the exact reverse dynamics - slowly roll-back the duties to absorb the price increases. With several elections round the corner in the lead-up to 2019, the political compulsions will be overwhelming.

One more reason to hold pause on any thoughts of a fiscal expansion.

4. Livemint editorial captures the wrinkles in India's mobile phone manufacturing surge,

India has also shown impressive growth in manufacturing smartphones, almost tripling the value of output from Rs18,900 crore in 2015-16 to Rs54,000 crore in 2016-17. This is expected to increase to Rs94,000 crore in 2016-17. But all these “Made In India” smartphones, including those from home-grown companies like Micromax and Karbonn, are only assembled in India. Smartphone companies import semi-knocked down (SKD) units, in which all the key high-value components are already soldered. The value addition happening in India was only 6.1% of the smartphone’s value in 2016... In the 2015-16 Union budget, the government increased the differential excise duty structure for mobile phones from the earlier 5% to 11%, which gave domestic manufacturers a benefit over imported phones. This move has managed to flip the share of imported mobile phones from 69% in 2015 to 33% in 2016.

5. FT points to an interesting October Curse with financial markets, captured by the graphic below.

6. I have never been a great admirer of corporate India's dynamism and claims that it can propel India to become an economic super-power. And it is not just because of the questionable corporate governance standards, but also because of its relative failure to produce truly world-class innovations despite numerous opportunities.

The telecoms sector always gets held up as the poster child of what unshackling India's corporate sector from the License Raj can yield. While the explosive growth of cellular telecoms over the past decade and half have been truly transformative, there is also a less gratifying side.

Here is Sundeep Khanna's lament in Livemint about the sorely deficient R&D spending of India's telecom companies,

It is safe to say that just as information technology (IT) services were the success story of the 1990s, telecom services have been the defining story of Indian business in the first decade of the 21st century. Sadly, for all its growth and penetration, the sector has thrown up little by way of research and development. Not a single breakthrough technology in telecom has come out of India, which should have served as the perfect crucible for experimentation... In the list of 50 top applicants that filed under the World Intellectual Property Organisation’s Patent Cooperation Treaty (PCT), a list dominated by telecom companies like ZTE Corp., Huawei Technologies and Qualcomm Inc., there isn’t a single Indian name. Even worse, a report by Thomson Reuters last year named Samsung, Huawei, LG, State Grid Corp. of China, ZTE, Qualcomm, Ericsson, Sony, NTT and Fujitsu as the top 10 global innovators in the telecommunications industry for 2015. No mention again of an Indian telco.

All the ingredients that experts say are needed to fuel research and development in the sector have been present in India, a large and rapidly growing market, demanding customers, profits aplenty, a phalanx of financing options and intense competition that should logically have spurred innovation. What’s more, it was evident to anyone who cared to look that in a business driven so much by technology, the barriers to entry could collapse overnight as it happened when Reliance Jio made its moves a year ago. The bloodbath that has ensued hardly comes as a surprise.

7. The use of satellite data on night lights in economic data analysis is on the rise. Two good articles - one on the use and limitations of the use of such data, and another on why the NASA data on India may not exactly represent what is being claimed.

8. FT documents the property market rebound in China,

Urged on by Beijing, 38 per cent of all bank loans issued in the 12 months to August were home mortgages, according to official data, and local governments purchased 18 per cent of all residential floor space sold last year as part of a drive to provide affordable housing, according to estimates by E-House China Research Institute. The result has been another heady boom in construction. Rome was not built in a day, but based on residential floor area completed last year, China built the equivalent of a new Rome about every six weeks... For China’s domestic economy, the world’s largest at purchasing-power parity, property investment directly contributed 10 per cent to GDP in 2016. When manufacturing sectors like steel, cement and glass and retail sectors like furniture and home appliances are included, the share is at least 20 per cent...

A survey by FT Confidential Research, an independent research service owned by the Financial Times, found that 32 per cent of families own at least one home that is vacant. An estimated 50m homes, or 22 per cent of the total urban housing stock, were vacant in 2013, according to the most recent data from the China Household Finance Survey led by Li Gan, economics professor at Texas A&M University.

9. Madhya Pradesh is experimenting with a new approach to Minimum Support Price (MSP). Instead, under the Bhavantar Bhugtan Yojana, of government itself making the purchases at the MSP, the farmers will be reimbursed the differential between the MSP and their sale price. The experiment is being tried out for a period of two months for eight crops. The sales will have to be done in registered agriculture markets and subsidy will be transferred to the farmer's bank account. To prevent traders from artificially suppressing the market, the government will determine an average sales prices, not only based on the prices in the State but also in two neighbouring states.

This is a likely more efficient approach. But like with all such reforms, given the several pathways to game the new system, the success lies in effective implementation.

10. Finally, the latest adventure in kritarchy comes by way of the Supreme Court's decision to ban the sale of fireworks in Delhi during the Diwali festival.

This is clearly grandstanding judicial activism since there is at least as much or more evidence that the important contributors to air pollution in Delhi lie elsewhere - burning of crop waste in Punjab and Haryana, construction activity and vehicle emissions.

India R&D spending fact of the day

From Janak Nabar in Livemint,

Huawei’s R&D expenditure (around $6.5 billion) is about the same or more than that of Indian industry, while Microsoft spends (around $12 billion) about the same as the Indian government.

Market decoupling graphic of the day

John Mauldin points to this graphic from Zero Hedge which contrasts the trajectories of economic uncertainty (Economic Policy Uncertainty Index) and equity uncertainty (VIX index).

The stunning divergence is one more data point to put to rest the lie that market valuations are a fair reflection of economic realities. 

Weekend reading links

1. Government intervention to make strategic purchases to both catalyse markets and lower prices is logical. The most cited example of such intervention in recent times has been the procurement of 770 million LED lights by 2019 as part of India's Domestic Efficient Lighting Program (DELP), which has resulted in a steep drop in the prices of LED lights.

Buoyed by the success, the government company, Energy Efficiency Services Ltd (EESL), is seeking to procure 5 million smart electricity meters and drive down prices. Livemint reports that L&T have won a Rs 13.61 billion contract to supply 5 million meters over three years to discoms in UP and Haryana at Rs 2722 a piece, 40-50% lower than the current market rate. 

Power distribution companies will not have to make an upfront investment to deploy these meters. EESL is investing in procuring smart electricity meters and the services of the system integrator. Utilities can pay back through savings resulting from enhanced billing efficiency and avoided meter reading costs. EESL will also appoint a firm, a “system aggregator”, to manage the installation of smart electricity meters and to collect and store data on power consumption for analysis.

A very rare example of innovation and big-scale public policy thinking in India. The challenge, in this case, will be to hold the supplier honest and make them deliver good quality meters, and have the "system aggregator" be able to actually collect and make available the required data for energy audit. The matter of getting stuff done. But a very good initiative. 

2. Much of the analysis about the ongoing movement against informality glosses over the demand side of the equation. Manas Chakravarthy writes in Livemint,

One consequence of the introduction of GST and some of the other measures to tackle black money will be increased market share for the corporate sector. Stockbrokers have been celebrating the opportunities opened up. A Citibank research report says: “The Indian government’s ongoing structural initiatives (and the GST rollout) will accelerate the transition toward the organized sector. Moves towards a less-cash economy, indirect tax changes through GST, direct tax compliance, e-commerce, and some progress on labour law reforms, among others, will prove disruptive to traditional structures in the medium term and result in accelerated formalization as well as economies of scale in the long term.” It’s no surprise that big business has backed these changes to the hilt.

Let me repeat what I have said earlier many times, the informal economy is not going to disappear. It will linger on and only gradually shrink over decades.

Formality introduces costs, which the producer will have to pass on to the buyers. But we need buyers who can afford to pay the higher price to access that good or service. This affordability can come only with increased incomes, a function of economic growth.

Barbers sitting on roadside and on makeshift arrangements offering haircuts for Rs 10-30 will form the vast majority of haircuts in India for the foreseeable future. In contrast, salons where the haircuts cost Rs 75-100 or more, likely to be in the formal sector, form only a very small proportion of haircuts. Governments can do whatever it wants to force these barbers to become formal, but they will not. The simple reason is that there is only so much demand that can be generated for salon haircuts! The shift to salons will happen only with economic growth.

3. In the best GST article I have read, Indira Rajaraman, draws attention to a weakness of the current GST architecture and how it affect the risk sharing mechanism in India's retail eco-system. She writes,

The principal culprit is the monthly frequency of reporting required under the GST (for businesses with annual turnover more than Rs75 lakh). Within each month, there are three dates in sequence for voucher uploading, consolidation and claims, with a daily penalty beyond deadlines crossed, added to interest on any tax credits denied. This formal voucher-based monthly reporting has dealt a death blow to the risk-sharing mechanism underpinning the efficiency of the Indian retail supply chain as we know it. And that is what has hit growth. Take a retailer of non-perishable items like garments or footwear. Retailers order a consignment from upstream wholesalers according to their best judgement of what clients will buy. The traditional practice was that if a retailer overestimated the appeal of a new style to his client catchment area, he returned unsold stock to the wholesaler, and finally paid the wholesaler a few months later only for his net purchase, net of returned stock.

Risk cover does best when risk is pooled across many locations with diversified patterns of incidence. The wholesaler is able to bear the risk of sale reversal because he can re-distribute returned stock. A new style in garments or slippers may lie unsold in one location, but fly off the shelves in another. Wholesalers in turn spurn retailers who return stock beyond some percentage limit of the gross purchase, thus leaving enough risk with the retailer to incentivize him to judge his market correctly and put in his best sales effort. If goods are defective, the wholesaler in turn returns the stock to the manufacturer, which again assigns risk to the only level where defects can actually be addressed.

When there is a switch to monthly reporting, a wholesaler uploads the initial gross sale to each retailer, with GST charged on a numbered invoice lodged in the system. Although the GST system does permit reversal of sale through issue of a credit note which can be offset against the next sale to the same retailer, it adds to the procedural burden, and is not something wholesalers are willing to touch. In effect, sale reversal has become impossible under GST, even for defectives. Retail buyers are now being asked to take a consignment at their own risk, and thereafter hold their peace. The traditional risk-sharing mechanism lies shattered.

Given that the retailer can no longer (in effect) reverse any part of an uploaded transaction, he minimizes risk by reducing his gross purchase from the wholesaler to the floor of his expected range of retail sales. This is what has hit growth. Wholesalers faced with reduced retailer offtake in turn place lower orders from manufacturers. Manufacturers have responded by sharply lowering production, some operating at as little as 25% of capacity.

She proposes doing away with the voucher uploading and matching process and replacing it with rigorous sample audits. I am inclined to agree.

4. A great stall is on in India's construction sector, the second largest employer after agriculture. Sample this,

For three consecutive quarters, the stalling rate in the realty sector has been in double digits, with the total value of stalled realty projects touching Rs1.27 trillion in the September quarter. The stalling rate (or value of stalled projects as a percentage of projects under implementation), at 12.7%, was at its third-highest level in nine years, only marginally better than in the June quarter, when the stalling rate hit a nine-year high of 13.3%. The commercial real estate sector has been the worst-hit, with a fifth of such projects getting stalled.

5. Talking of stalling, stalled infrastructure projects are no longer news. The latest on them shows limited progress in addressing the chronic problem. The value of stalled projects reached its highest level of Rs 13.22 trillion for the September quarter and stalling rate was 13.3% of all projects under implementation.

The reasons for stalling were the usual suspects - lack of clearances, fuel supply, finances, land etc.

A total of 39.04% of the projects are in the power sector and 25.59% in manufacturing. But the most disturbing news is in the declining new investment announcements. Sample this,

The value of new private sector project announcements in the quarter ended September was Rs31,000 crore. This value was Rs1.79 trillion and Rs1.69 trillion in the quarters ended September 2016 and 2015. 

6. This is a nice graphic that captures the fact that average commuter trip lengths rise with increase in city population size.

The article laments about the political difficulty of increasing urban mass transit fares and the resultant subsidy gaps.

While raising mass transit fares periodically is important, we should also bear in mind that farebox ratios are less than 50% in most metro rail systems across the world. In other words, more than half the operating expenses are subsidised. Therefore a more serious issue for consideration than cost-recovery may be to mark metro ticket prices as a percentage share of the median commuter wages.

The report states that the Railways subsidised Mumbai suburban railway commuters to an extent of Rs 33.94 bn over the past three years. That's not at all bad. An annual subsidy of Rs 11.3 bn for ferrying over 2.5 bn commuters (or 7.5 million per day), especially when seen as the cost of keeping them off Mumbai's roads, is actually a very good deal! In terms of efficiency, it would easily be the most cost-effective urban mass transit operation anywhere in the world. Managing a city is not just about recovering costs, it is about creating the conditions for creating growth, jobs, and wealth. And Mumbai mass transit does it better than most other enablers that the government has put in place.

7. Just like with anything else, too much competition is bad. As Andy Mukherjee writes, India's telecoms market is the best example. The race to the bottom with call and data tariffs have left everyone bleeding, and threatens to make this the latest addition to the bad debt problem for Indian banks. Mukherjee suggests that the carnage will not stop till the industry undergoes more consolidation and failures and reduces to four players.

However, I do not think that even then it is unlikely to be much different. As I blogged earlier, the elimination of interconnect charges on grounds that it would lower profits may not, in retrospect, turn out to have been a very good decision. 

8. Aeon has a fantastic essay on the evolution of higher education system in the US. It talks about the role of property speculators trying to use the College/University as a cultural centre and anchor to attract property buyers; competition among towns, state, and even church to establish colleges; the modest government funding forced colleges to charges fees and thereby compete to make college valuable for students; the limited regulation beyond grant of charter which allowed colleges lot of autonomy to innovate to attract students; the practicality associated with attracting middle class fee-paying students meant offering job-oriented course-work (engineering, agriculture etc) and accord importance to things like football.

And for those countries trying to replicate the US model of higher education, the author has this advise

Since it’s a system that emerged without a plan, there’s no model for others to imitate. It’s an accident that arose under unique circumstances: when the state was weak, the market strong, and the church divided; when there was too much land and not enough buyers; and when academic standards were low. Good luck trying to replicate that pattern anywhere in the 21st century.

9. The week Richard Thaler won Nobel Prize in Economics, comes this report from SCMP on the use of nudges (or, are they "shoves" here?) to get people to pay their taxes

Local governments have been told to set up name-and-shame databases – which will be searchable by anyone – by the end of the year... In the southern city of Guangzhou, the personal details of some 141 debt defaulters have so far been displayed on screens in buses, commercial buildings and on media platforms at the request of local courts. Meanwhile in Jiangsu, Henan and Sichuan provinces, the courts have teamed up with telecoms operators to create a recorded message – played every time someone calls – for those who fail to repay their loans. The message tells the caller: “The person you are calling has been put on a blacklist by the courts for failing to repay their debts. Please urge this person to honour their legal obligations.”

10. Finally, the award for risk diversification best practice has to go to LIC. It has been reported to have made a bid for shares worth Rs 7000-8000 Cr in the IPO of reinsurer General Insurance Corporation (GIC) Re. Talk about insurer buying exposure into a reinsurer who also insures some part of LIC's own portfolio! Or is it a case of LIC as the buyer of last resort in disinvestments.

Plumbers, police, and hotspots

Now Chris Blattman has new paper on policing which is, willy-nilly, being cast as raising doubts on "hotspot" policing - use of digital technologies for intensive policing of areas where crime is concentrated. 

The paper finds that while such policing "deters crime and violence" in those areas and "reduced the most serious violent crimes" (rape and murder) in the aggregate, it had limited impact on the "number of total crimes deterred". But it found "spillovers", "pushed property crime around the corner" etc. The tone of the paper (and you can just browse to feel what I mean) unmistakably gives the impression that the paper evaluated "hotspot" policing and found limited benefits. 

Given the framing, it is only natural that people will raise doubts on "hotspot" policing. I can also imagine this paper triggering off more research on distant concerns like spillovers. While nothing as damaging as this can happen with this paper, the costs of such digressions are non-trivial.  

This is all very unfortunate and a testament to the state of development economics research. I actually think that the paper's primary endeavour itself is questionable. Why do we need to test the efficacy of "hotspot" policing?

To answer this, we need to deconstruct "hotspot" policing. There are two elements here. One, prioritising and targeting work. Two, using digital technologies (data analytics and visualisation dashboards) to help with decision-support on the prioritisation. 

Do we need evidence about these two elements? In more simple terms, in a system with scarce resources and several competing needs, isn't it a natural order of things to prioritise them using the most effective reporting and monitoring mechanism possible? 

Have we ever sought evidence on whether great Dashboards are a step in the right direction in the corporate world? Did the first set of corporate users demand evidence from IBM before placing orders for Cognos?

I see Dashboards as a logical progress in the transition of data management from the far less user-friendly stages of massive paper Registers and the confusing array of rows and columns of Excel sheets. Registers and Excel sheets contain data. Dashboards contain information. 

There are two logical criticisms to "hotspot" policing. One, given that actual decisions get taken at smaller jurisdictions, the human agents may have the bandwidth to be able to have a good real-time mental picture of the hotspots. A Station House Officer or Police Inspector, especially in urban areas, who has served for a couple of months, should have a fairly good idea of the high crime incidence areas, people, and categories. So why need a "hotspot" map? Two, even if the police manager is able to prioritise, he cannot, for contextual reasons (say, political complusions or there are too many high crime areas and too few constables to spare), deploy staff as he/she wants. What is the need of something that cannot always be acted on?

The responses are also two-fold. One, it may so be that police managers already have a graphic mental knowledge of all this stuff. But a mental map is a private information. Instead, information captured in this manner is amenable to effective monitoring across the organisation and is therefore a public information. This is true of any organised hierarchical system. Two, the objective should not and cannot be to have precise prioritisation and its implementation by all police managers. Even if a small share of them start using it, which is most likely in any large system, in a decidedly second-best manner, that itself would be a big progress. We would have set the stage for diffusion of an undoubtedly more efficient approach to policing. Given the weak state capacity in police systems, any improvements in monitoring capacity enhances administrative efficiency in the aggregate. 

Or the researchers could claim that they have generated evidence which can help limit the damage with fancy ideas which lead to massive wasteful spending. But how costly is a freeware application like this, this, and this that police jurisdictions can use to translate their data to actionable information? 

I see several pathways to change. One, some of the more enthusiastic police managers in a system find great value in using such technologies to prioritise and monitor their beats. Positive deviances emerge. Two, as Justice Brandies said, sunlight is the best disinfectant. Hotspot applications can shine light, bright and deep, into the crime data collected by police systems. Actionable information emerges. At least some insiders and outsiders can learn and act. 

I am unambiguous and unashamed in support of "hotspot" policing. All policing jurisdictions should, among other things, strive for spatial (and on temporal and human dimensions too) prioritisation and targeting of their policing efforts and they should use technologies like "hotspots" and other types of Dashboards! Of course, needless to talk about all caveats of data privacy and data biases, and the need for their mitigation.

This is not all that is bad with the paper. Spending too much research effort dwelling on displacement is a psychologically misleading illusion. Talk of constructing a fictitious straw-man and then refuting it! Why did we ever think that there would not be any displacement? Isn't it natural for thieves to move to the margins if an area suddenly becomes more intensively policed? Who said crime fighting is a binary game? It is far from the case that if we focus efforts in an area, crime will be eliminated.  

Policing is a repeat game. Actually, police officials, unlike economists, deeply internalise this plumbing reality. Focus on the existing hotspots and reduce incidence there. Respond to the emergent trends and redeploy. Keep iterating and aggregate crime will reduce gradually. If available, even use machine learning applications that have predictive analytics to help double down on the displacement locations. And alongside, also take all the other complementary steps required, not just including those by the police, to address crime. At least some police jurisdictions will have the good fortune of confluence of positive factors that contribute to the emergence of positive deviances in a few years. 

And in several policing concerns like traffic safety, where accidents happen more because of location characteristics and are less likely to be "displaced", just "hotspots" visualisation can be useful as decision-support. 

The most disappointing part comes somewhere near the end (italics mine),

But if crime is easily displaced, then targeting, coordinating, and concentrating resources in high-crime places may not be the right approach after all. Rather, it might be wiser to target the specific people who commit crimes or particular behaviors. Displacement may be inherently less likely than in place-based approaches. This is the spirit of focussed deterrence, which identifies the small group of people who commit serious crimes and use threats and incentives to keep them from offending (Kennedy, 2011). This is also the spirit of cognitive behavioral therapy, which fosters skills and norms of non-violent behavior in high-risk young adults (Heller et al., 2017; Blattman et al., 2017).

In an ideal world, we need to address the underlying socio-economic reasons for crime and several other dimensions, including focusing on the most riskiest people. Many of these dimensions are beyond the control of police departments. And in the real world, we all know the difficulty, even impossibility, of breaking down silos and addressing problems in a comprehensive manner. Should we wait for that ideal world to arrive before we try this out?

Who says "hotspot" targeting trades-off police system resources with "person" targeting? How can we say that it should at all be one or the other? Wouldn't measures to target specific people become likely more effective when the deterrent effect on places is higher and vice-versa? 

This is pulling stray research strands, the only intersection being that they were all done by the same researcher, and generating a grand policy narrative about addressing crime and violence. Frankly I just don't have the energy to go on. 

Talk of writing a paper on the obvious! And even making a splash out of it! Why is academic research so plumbing-free?

Bubbles, bubbles everywhere, waiting to burst?

The big lesson for central banks from the bursting of the sub-prime mortgage bubble was that monetary policy has to go beyond narrow focus on price stability and also address financial stability. 

It is therefore remarkable that quantitative easing continues unabated even as asset prices are frothing across markets - bonds, stocks, property, and even cryptocurrencies! In some cases like Sweden, as Zero Hedge points out, real housing prices are well past their highest levels since 1875! In fact, they are at more than double their previous high. 

And despite this, the Riksbank prefers to continue monetary accommodation by retaining rates at minus 0.50%! Of course, it does not help that its monetary policy is locked into ECB's monetary policy stance. 

The real estate markets in Canada and Australia are not far behind. And junk bond spreads in the US are threatening to touch their lowest in the past two decades. Credit spread for investment grade bonds is just a percentage point! Long-term global real interest rates are at historic lows. 

In the US, the Shiller CAPE, which compares the S&P 500's current price to the 10 year average of earnings, stands at a ratio of 31, indicating that stocks are about 50% over-valued on historic average, a figure exceeded only once in the past 60 years! 

In fact, over a longer historical sweep, the average stock is trading at 73% above its historical average, higher than all but two occasion since 1880 - just before the Great Depression and the run-up to the 1999 dotcom bubble bursting.

It is a moot point as to what is the main driver of the extraordinary low interest rates in developed countries. While on the supply-side the global savings glut, arising from shifting demographics, and on the demand-side structural changes have lowered the cost of capital investment, it cannot be denied that the QE has hastened the downward trend of real interest rates.  

While QE was understandable when the world economy was tottering in 2008, it is surely well past time to step back. But the reluctance of central banks to roll back the extraordinary monetary accommodation is yet more proof that central banks are unlikely ever to be able to take the punchbowl away when the party is on.

Isn't this a compelling enough reason why there should be dynamic macro-prudential regulations that act as automatic counter-cyclical measures to lean against the wind when such bubbles are inflating?

Update 1 (19.10.2017)
The graphic below shows why the equity and bond markets are operating at pretty much the tail-end of the spectrum in terms of valuations.

Yet, despite the froth, short-term implied volatility has never been lower for decades.