I have lived in the City of Baltimore for 6 months now.  The City faces challenges. It needs to hire more police officers and it needs to upgrade the infrastructure of the public schools and upgrade public transit.  The City will be expected to also contribute $ to enact the education recommendations embedded in the Kirwin Report.  At a time of historically low interest rates, should the city be issuing more bonds? There is a demand for such bonds.  The city's bond rating appears to be pretty good and there isn't a large risk premium associated with not having a perfect bond rating.  

So, why isn't Baltimore issuing more bonds?  One possible explanation is that the City would prefer to engage in a game of "chicken" and allow conditions to deteriorate and wait for the state and the federal government to transfer $ to the city.

If a city must borrow money to do projects, then (ignoring default risk) this provides a strong incentive for such entities to carefully prioritize public goods projects  and to implement them in a cost-effective way.

I recognize that raising taxes is a substitute for issuing debt.  I also understand that land owners will vote against debt financing of local public goods improvements if they believe that the present discounted value of the new public goods will be less than the PDV of the tax increase. Intuitively, if a government issues debt and uses the money unwisely then land prices in the city will decline because  future taxes will have to go up to pay off the debt and the interest owed.

If salience factors preclude new tax hikes and if the projects I list above have a positive PDV in terms of benefits, then issuing bonds in a low interest rate environment would be a prudent strategy for financing these public investments. 

As the Chinese leadership uses it power to try to stop the coronavirus contagion, does this horrible event offer a test of Barro's 2006 QJE paper?   As I understand his paper,  asset prices reflect the fact that there is a positive probability of large drops in a nation's output.  To compensate investors for such low probability but dangerous risk, there has to be  an equity premium (i.e the rate of return on stocks versus safe bonds).

Here is a graph of the last 12 months of the Shanghai Index.  The index has fallen around 10% since early February 2020.  Is this an accurate representation of the expected present discounted value of lost future profits for Chinese firms going forward?

In this Big Data age, what do we now know about urban government productivity?  Whether the city is Baltimore or Chicago or San Diego, when a city spends an extra dollar on public goods such as street safety or public transit, how much local public goods are produced?  This is a surprisingly difficult question to answer and in the next series of blog posts, I will argue that this "opacity" benefits several interest groups including the Mayor, the urban government and the public sector unions.

Back in 2017, I co-authored a paper that was published in the Journal of Public Economics that investigated the productivity of the public transit bus sector in over 100 cities over a 20 year period.

A more productive public sector has a lower average cost per bus mile.   There is a simple Leontief production function producing bus miles.  The inputs are;  a bus, some gasoline to drive the mile and a driver. Given that the bus and gasoline are sold on world markets, there is a single price for those inputs and the only source of variation in productivity is the price of labor.  I believe that quality variation is small here. A bus driver is a bus driver.  We document that where public sector unions are more powerful that average costs of service provision are higher.    We document that when cities replace a progressive mayor with a Republican mayor that these costs decline.  Urban politics matters in determining the price of local public goods.  Progressive cities face higher prices for local public goods.

The open question here is what is the extra quality and quantity of local public goods produced when an extra $ is spent?  Does the answer differ across cities with weaker and stronger local unions? Does the answer differ depending on the city's demographics?  For street safety and fire protection and public education, what is the marginal product per dollar spent?  Rick Hanushek's work offers one perspective and recent work by Bo Jackson and co-authors  offers an alternative perspective.

Today, cities are publishing data on teacher salaries and school level test scores.  Cities are publishing data on total pay (salaries and overtime) for each fireman in each year.     Read our 2019 report studying public pay in Baltimore, Boston and NYC using public Big Data.  

From such data, can economists estimate production functions of local public goods to infer the marginal product and average product of these public employees per dollar spent?  (the bang per buck condition familiar from intermediate microeconomics).  I claim that we cannot and that this creates "opacity" as economists cannot judge whether taxpayers are getting a good deal when the local government devotes tax $ to greater public employment.

In the next series of blog posts, I will sketch out additional data that urban governments should post to help to build confidence that urban governments are delivering quality service and to be held accountable to skeptical tax payers (and suburbanites considering moving to the cities).

The theme of these blog posts will focus on how to build trust in urban government through transparency and accountability.   Analytics are being used in pro-sports (Money Ball) in benchmarking academics (Google Scholar) and in business (Amazon is a trillion $ company because of its use of analytics).  I will propose a research endeavor to slightly disrupt business as usual in the urban public sector. 

For PHD economists, the research agenda here is to measure a structural local public goods production function in the presence of a heterogeneous production function and the possibility of x-inefficiency such that the equilibrium L/K ratio lies inside the production possibility frontier. 

I just read Jason Furman's review of Ezra Klein's new book Why We're Polarized.    I would like to offer a simpler economic explanation.   Every economist is taught that a necessary condition for trade through markets to yield a mutually beneficial outcome is that we must agree on who has the property rights.   When I enter a Starbucks,  I want a coffee.  Starbucks owns the coffee beans and the capital stock and has trained the talent to make me a coffee.  The price that I buy the coffee from the owner of the coffee is such that the trade makes both of us better off.  Yes, I would prefer to pay $0 for the coffee but at that price Starbucks wouldn't sell me the coffee.

 Rising polarization is taking place because there is now a fundamental disagreement across our society concerning who has the property rights to different resources.  Whether the issue is the right to emit carbon, free health care, free college, admissions to Harvard, free health care, in each of these cases a fight is brewing about property rights.  The owners (or the tacit owners) of such property recognize that there will be a large negative income effect if the transfer of property takes place and they are digging in to protect their claims to what they have always controlled.

When "property rights" redistribution enters the policy discussion, game theory becomes the key discipline for analyzing what will be the outcome. Who can make a credible threat? How are coalitions formed?

Given this setup,  would I predict that all rich people will approach the redistribution issue in the same way?  Tom Steyer is very rich and he supports many of the progressive positions.   His wealth portfolio is unlikely to be hurt by carbon taxes.  Given that he is very rich, he can afford to sacrifice some of his $ to achieve his social goals. 

Economists can play a productive role here by nudging the public to be explicit about what are your economic property rights?  Given the balanced budget condition, can all of these "rights" be consistent at a given point in time? 

Back in 2004, Dora and I published a paper documenting that from 1940 to 1990 the estimated value of a statistical life in the U.S grew faster than U.S per-capita GNP.    Other studies from Taiwan and India have documented a similar result.

These findings have implications for China today and risk regulation policy in the face of the contagion risk.  As China has grown richer, the value of risk avoidance rises.  There is a greater aggregate demand for safety.  The CCP thus has a strong incentive to deliver safety.  This same logic was at the heart of my work with Siqi Zheng on air pollution regulation. Read our 2017 paper in JEP.

In the case of the Coronavirus,  the Chinese state appears to have been slow to recognize the urgency of the issue.  How much of this slow response is due to a desire to not appear weak and panicky to the West (and President Trump). An alternative hypothesis returns to Hayek's view on how information flows in a system and asks whether the local leaders in Wuhan feared punishment by the Beijing bosses for panicking and thus delayed sharing bad news with the upper level leaders in Beijing. This raises the issue of how the CCP treats Type 1 versus Type 2 errors. Would the Central Beijing Government prefer to hear news of "false alarms" from the local areas or does it prefer being "slow to react" to a real crisis?  The rising VSL in China would predict that the Central Government would create incentives to trigger the "false alarm" scenario such that when there is any chance of a major risk event that the central government is notified and uses its autocratic power to take action.