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Environmental and Urban Economics



Matthew E. Kahn , Professor of Economics at USC



Updated: 2018-01-21T10:23:26.443-08:00

 



REPEC's Rankings of USC Economics

2018-01-21T10:23:26.779-08:00

As we enter the recruiting season for both new MA and PHD students and recruiting new faculty, it is useful to collect some facts about where USC Economics ranks.   I find that vanilla rankings such as US News and World Report are backwards looking and based on outdated information.  So, permit me to present some facts based on REPEC;We are ranked #20 among U.S economics departments (Columbia is double counted).We are ranked #23 in the world among research universities.  (I"m not counting 4 non-universities ranked above us).   We hold this same rank if you restrict to our publications over the last 10 years.In Econometrics,  we are ranked #7 in the world.In natural resources economics, we are ranked #5 in the world (and I'm ranked #2!).  In terms of individual economists, we hold the following ranks among the world's 55,000 ranked economists.   So, Hashem is the #24 ranked economist in the world.  Impressive!2424. M Hashem PesaranDepartment of Economics, University of Southern California, Los Angeles, California (USA)125Joshua AizenmanDepartment of Economics, University of Southern California, Los Angeles, California (USA)342Matthew E. KahnDepartment of Economics, University of Southern California, Los Angeles, California (USA)584Cheng HsiaoDepartment of Economics, University of Southern California, Los Angeles, California (USA)747747  Kevin J. MurphyDepartment of Finance and Business Economics, Marshall School of Business, University of Southern California, Los Angeles, California (USA)815Arie KapteynCenter for Economic and Social Research, University of Southern California, Los Angeles, California (USA)1293Vincenzo QuadriniDepartment of Finance and Business Economics, Marshall School of Business, University of Southern California, Los Angeles, California (USA)1425John StraussDepartment of Economics, University of Southern California, Los Angeles, California (USA)1660Hyungsik Roger MoonDepartment of Economics, University of Southern California, Los Angeles, California (USA)1732Geert RidderDepartment of Economics, University of Southern California, Los Angeles, California (USA)2125Romain RanciereDepartment of Economics, University of Southern California, Los Angeles, California (USA)2377Jeffrey B. NugentDepartment of Economics, University of Southern California, Los Angeles, California (USA)When you add up the USC Economists sitting at the Economics Department, Marshall, CESR, the Price School and the Schaeffer Health Economics center, we collectively represent a thriving research community.As you ponder these facts, keep in mind that this is a lower bound relative to what we will achieve over the next 5 to 10 years.  We achieved these accomplishments despite the fact that USC Economics has only 1 endowed chair.  We are the largest major on campus and our MA program is thriving.  [...]



The Dynamics of the Marginal Cost of Reducing Air Pollution in Beijing, China

2018-01-15T08:09:03.946-08:00

The NY Times has published a very interesting piece on the unintended consequences of Clean Air regulation in China.   The piece makes some excellent points and then at the end of the piece it takes a punch at the autocratic state.   Permit me to make some economics points that build on the piece.The author is correct about the short run costs of compliance with the regulation but in the medium term and long term several market and firm level adjustments will take place that will sharply reduce the cost of compliance with this regulation. For example, the author says that in the short run that the supply of natural gas (the clean fuel) is inelastic so rising demand for this fuel raises the price of natural gas and this raises costs for small businesses.  But, Alaska has a major LNG port and can ship such gas to China.  This will soon occur and the medium term supply of natural gas to China will be much more elastic and thus higher demand will not translate into higher prices for this clean fuel.Second, the author does not discuss industrial organization. As the price of energy rises, there will be some firms in the same industry who figure out how to produce more efficiently and thus will suffer a smaller marginal cost increase induced by the regulation. The author is implicitly assuming that energy is "Leontief" in the isoquants and that all firms in the same industry have the same production technology.  This is false. In our work on China, the median urbanite wants cleaner air --- while there is no free lunch the government is responding to this pressure by increasing the supply of such public goods.  The author of this piece may be correct that the "little guys" in business bear the incidence of this regulation but this doesn't mean that the regulation is bad.  I think that PHD economists should further explore this economic incidence point.Here are my relevant papers on this topic. Siqi Zheng & Matthew E. Kahn, 2017. "A New Era of Pollution Progress in Urban China?," Journal of Economic Perspectives, American Economic Association, vol. 31(1), pages 71-92, Winter. Matthew E. Kahn & Pei Li & Daxuan Zhao, 2015. "Water Pollution Progress at Borders: The Role of Changes in China's Political Promotion Incentives," American Economic Journal: Economic Policy, American Economic Association, vol. 7(4), pages 223-242, November. Zheng, Siqi & Kahn, Matthew E. & Sun, Weizeng & Luo, Danglun, 2014. "Incentives for China's urban mayors to mitigate pollution externalities: The role of the central government and public environmentalism," Regional Science and Urban Economics, Elsevier, vol. 47(C), pages 61-71. Sun, Cong & Kahn, Matthew E. & Zheng, Siqi, 2017. "Self-protection investment exacerbates air pollution exposure inequality in urban China," Ecological Economics, Elsevier, vol. 131(C), pages 468-474.[...]



How Will the American Economics Association Adapt to Climate Change?

2018-01-04T18:36:12.028-08:00

Roughly 15,000+ economists are trying to get to Philadelphia today for the annual ASSA meetings.   In a typical year, I greatly enjoy the meetings.  It is a place to see old friends, mentors, past students, co-authors and to attend sessions, meet with book editors and talk about economics.  This is a special year for USC Economics this year because we will hire 3 new PHDs to join our faculty.  As we upgrade our department, we need "new blood".  We will be interviewing 50 people.

The challenge we face is that the ASSA meetings take place in the first week of January and they typically rotate between Boston, Chicago, Philly (and warmer cities including Atlanta, Washington Dc and San Diego).  The cold winter cities offer cheap hotels and decent airports but as the winters grow harsher there is rising discontent with bringing thousands of us into "harm's way".

UCLA has moved all of its interviews over to Skype.  (UPDATE, I'm wrong about this -- some of the UCLA interviewers will be listening in on Skype).  I think this is brilliant.  What is lost by not having face to face contact for a 25 minute interview? My hunch is nothing.  So, the Economists will adapt by either moving the timing of the conference, the city or an unraveling of the conference as more of the participates who are mainly there for interviewing Skype in.

A general equilibrium point.  A young reduced form researcher seeking to answer the question;  "how is bad weather affecting the economy"  Would run a regression by year of the form:

Total Conference revenue_t  =   constant + b1*bad weather_jt  +   b2*great city dummy_j   +  U_Jt

so we expect that b1<0 and="" b2="">0 as great cities such as San Diego and San Fran generate more business.

The b1 would be interpreted by some reduced form researchers as the "cost of climate change" but let's be more specific, the $ not spent in Philly this weekend (because economists have chosen to stay home) will be spent in the economist's origin cities.  The reduced form researchers ignore such cross-elasticities.  Why?   There are too many cross-elasticities and to properly model them would require a structural model.   So, while "b1" can be estimated and it is of interest to Philly's local boosters -- it really isn't that interesting of an economic parameter.  The $ that would have been spent in Philly had the weather been good does not vanish when the weather is bad, it is spent elsewhere.



Undergraduate Economics Should Focus on Revealed Preference Logic

2017-12-20T07:19:51.006-08:00

In December 2016, I wrote a short Amazon book on the economics of revealed preference.  I wrote this book after teaching "Econ 101" at USC.  While I have taught Econ 101 on and off for 25 years (starting back at Columbia University), I have now concluded that the right way to teach this class is to cast the economist as "a detective".   We observe clues about a person's "type" based on the choices we observe her make when she is confronted with different choices sets (that vary due to her income changing and the relative prices she faces shifting).  Under the assumption that a person's tastes do not change much over time, we can begin to pin down a specific person's tastes.

An example of my book's logic.   Sally is offered a meat pizza at a price of $15 and she doesn't buy it.  The next day, she is offered a meat pizza for a price of $2 and she doesn't buy it.  The next day, she is offered a meat pizza for 1 penny and she doesn't buy it.   We begin to deduce that Sally is a vegetarian.    While we don't know Sally, we observe Sally's market choices and we learn about her.  This is the the theme of my book.  We take revealed preference seriously and thus are able to "reverse engineer" what must be the preferences of the consumes whose choices we observe.  This is the right way to teach econ 101.  Data combined with theory yields insights about diverse peoples' types.

Note that this is very different standpoint then what is usually taught in intermediate micro where I tell you Sally's preferences and budget constraint and you grind out her optimal consumption bundle using simple calculus or geometry. I argue in my 2016 book that we should solely study the "inverse problem" focused on partially identified models.  What do I learn about you based on the subset of choices I observe you make?





A Quick Summary of My Published Work in 2017

2017-12-20T05:42:11.436-08:00

Now that 2017 is wrapping up it might interest some people to hear why I choose to work on some research questions.  For each paper I published in 2017, I offer a few "big picture" comments to explain what questions motivated the research.2017 Articles Jerch, Rhiannon & Kahn, Matthew E. & Li, Shanjun, 2017. "The efficiency of local government: The role of privatization and public sector unions,"Journal of Public Economics, Elsevier, vol. 154(C), pages 95-121. Delmas, Magali A. & Kahn, Matthew E. & Locke, Stephen L., 2017. "The private and social consequences of purchasing an electric vehicle and solar panels: Evidence from California," Research in Economics, Elsevier, vol. 71(2), pages 225-235. Dora L. Costa & Matthew E. Kahn, 2017. "Death and the Media: Infectious Disease Reporting During the Health Transition," Economica, London School of Economics and Political Science, vol. 84(335), pages 393-416, July. Bunten, Devin & Kahn, Matthew E., 2017. "Optimal real estate capital durability and localized climate change disaster risk," Journal of Housing Economics, Elsevier, vol. 36(C), pages 1-7. Matthew E. Kahn, 2017. "Will Climate Change Cause Enormous Social Costs for Poor Asian Cities?," Asian Development Review, MIT Press, vol. 34(2), pages 229-248, September. Sun, Cong & Kahn, Matthew E. & Zheng, Siqi, 2017. "Self-protection investment exacerbates air pollution exposure inequality in urban China,"Ecological Economics, Elsevier, vol. 131(C), pages 468-474. Siqi Zheng & Matthew E. Kahn, 2017. "A New Era of Pollution Progress in Urban China?," Journal of Economic Perspectives, American Economic Association, vol. 31(1), pages 71-92, Winter.1.  It is difficult to rank the productivity of local governments in providing services at a point in time or to compare the same city's productivity over time.  We argue that the average cost of moving a bus a mile offers an "apples to apples" metric for ranking local governments.  We study when governments outsource to private entities and how such outsourcing affects the average cost of service delivery.  We explicitly model the endogenous privatization choice.2.  Solar panels and EVs are complements.  It is no accident that Tesla and Solar City have merged into one company.  We use existing data to study the joint spatial distribution of the purchases of these "green products".   We discuss how innovations in financing these durables affects their annual "affordability".3.   How does the NY Times decide what to report?  Major cities report their death rates from infectious diseases several times a year. Such dynamics in this "objective reality" provide a benchmark for studying whether the media reports "good news".  During times of slow linear progress in death rates, the media doesn't cover the story.4.   The popular media routinely publishes pieces arguing that coastal real estate in cities such as Miami is doomed because of sea level rise caused by climate change.  If forward looking developers and real estate owners are aware of these emerging risks, then this alters development patterns and capital maintenance patterns.  The net effect of such supply side decisions is a more elastic supply of housing and less ex-post damage caused by the sea level rise that ultimately occurs. The New York Times and other (i.e Joe Romm) implicitly assume that the capital stock in at risk places is infinitely lived. While this capital is durable, it has a finite (and endogenous) life.  One way to adapt to climate change is to have a  less durable capital stock such that we retain the option to rebuild on higher ground.  This supply side approach to studying real estate in the presence of emerging spatial risks has not been previously studied.5.  This piece reviews my thinking about h[...]



Optimistic Findings about California Air Pollution Trends During the Fire Season

2017-12-07T16:33:36.591-08:00

The recent Los Angeles fires have been quite scary.  When I'm scared, I start to run new regressions.  I take daily PM2.5 air pollution data from the EPA and keep the subset of observations for the following states; California, Arizona and Nevada.  I use data from the years 2000 to 2017.   I merge in data on daily wind speed and average temperature.  I create two key variables;Fireseason = 1 if the day is in September, October, November, Decembertrend  =  the monthly time trend (so there are 17 years and 12 months per year so this variable takes on the values 1 to 12*17)inter  =  Fireseason*trend   , this interaction term tests if the monthly time trend differs during the fire season.So, for 152 monitoring stations in Arizona, California and Nevada; I am running a regression where the Y variable is the log(PM2.5) on a given day.  I include monitoring station fixed effects and I regress this on a monthly time trend (t),  the fireseason dummy (see above) the time trend during the fireseason months and the climate variables (log wind and log average temperature).. areg lmean t inter  fireseason lwind lavgtemp , absorb(idno) cluster(idno)Linear regression, absorbing indicators         Number of obs     =    405,388                                                F(   5,    151)   =      47.76                                                Prob > F          =     0.0000                                                R-squared         =     0.2775                                                Adj R-squared     =     0.2772                                                Root MSE          =     0.6412                                 (Std. Err. adjusted for 152 clusters in idno)------------------------------------------------------------------------------             |               Robust       lmean |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]-------------+----------------------------------------------------------------           t |  -.0018944   .0002363    -8.02   0.000    -.0023612   -.0014276       inter |   -.001042   .0002175    -4.79   0.000    -.0014717   -.0006123  fireseason |   .2643525   .0310733     8.51   0.000     .2029578    .3257471       lwind |  -.1425646   .0743011    -1.92   0.057    -.2893687    .0042395    lavgtemp |  -.0306948    .072866    -0.42   0.674    -.1746633    .1132738       _cons |   3.13[...]



The PHD Economics Cohort from 1993

2017-12-04T15:11:15.183-08:00

The Repec competition continues.  I do not believe that Martin Browning is part of our cohort.  1993RankAuthorScore1John Michael van ReenenCentre for Economic Performance (CEP), London School of Economics (LSE), London, United Kingdom2.222Florencio Lopez-de-SilanesSKEMA Business School, Lille, France2.513James Alan RobinsonHarris School of Public Policy, University of Chicago, Chicago, Illinois (USA)3.444Charles I. JonesGraduate School of Business, Stanford University, Stanford, California (USA)4.335Martin James BrowningDepartment of Economics, Oxford University, Oxford, United Kingdom6.886Serena NgDepartment of Economics, School of Arts and Sciences, Columbia University, New York City, New York (USA)7.317Thomas PikettyParis School of Economics, Paris, France7.68Matthew E. KahnDepartment of Economics, University of Southern California, Los Angeles, California (USA)7.989Casey MulliganDepartment of Economics, University of Chicago, Chicago, Illinois (USA)National Bureau of Economic Research (NBER), Cambridge, Massachusetts (USA)11.7510Mike WrightBusiness School, University of Nottingham, Nottingham, United KingdomRepec has informed me that my rankings "peers" are:Similarly ranked authorsThese peers are ranked around you and are listed in random order:Gert G. WagnerMartín UribeLaurence BallAthanasios OrphanidesAndrew AbelRoger B. MyersonRichard H. ClaridaJason ShogrenHarvey RosenEdward E. LeamerMarcel FratzscherThomas R. PalfreyViral V. AcharyaGiancarlo CorsettiNorman V. LoayzaDavid M. CutlerValerie Ann RameyHal Ronald VarianJong-Wha LeeAndrew W. Lo[...]



College Admissions at Elite Schools and the $500,000 Endowment Per Student Cutoff

2017-12-04T07:17:58.701-08:00

Under the pending Trump Tax Plan, Universities whose endowments are above $500,000 per student will face an endowment income tax of 1% a year.  A $7 billion dollar school would pay roughly $10 million dollars in cash (that's a lot of Assistant professors slots).  Holding a university's endowment fixed, if this school increases its student population by 20%, it will be less likely to face this tax threshold.  From the link above, I see that Duke, UPENN, Columbia and University of Chicago are all hovering around the threshold.  I predict that they will be admitting more students in the near future.

My son is a junior in high school so this incentive effect is of interest to me.

UPDATE:  This post has been updated to correct my mistake.  The tax is on endowment income (not wealth).  I thank USC Price Professor Nick Duquette for updating me. 



How "Inelastic" is the Demand to Live in California?

2017-12-03T07:46:13.682-08:00

Given California's high taxes on those who are well paid, such individuals keep 45% of each dollar they earn.  If such a person lived in Texas, he might keep 60% of each dollar earned.   President Trump's new tax proposal will further raise the tax price of living in California.  If state and local taxes are no longer deductible from federal income, then the tax price will rise sharply.     Who will bear the incidence of this tax?  Will even progressive voters in California demand a smaller government?  Will UCLA and the other public schools suffer?  Will the rich now start to move to lower tax areas or does CA's unique amenities keep people here despite the high tax?



A Busy Tuesday at USC Economics

2017-11-26T17:17:01.856-08:00

At USC Economics,  I (in my role as department Chair) have a busy schedule. We are hiring new faculty, creating new curriculum and engaging in fundraising.  Each day brings new challenges and new opportunities.   On  Tuesday, I will be interacting with our talented majors outside of the classroom in two different events;

Noon:  Lunch with Undergraduates

6pm  The Economics of Bitcoins

A department chair is a type of cheerleader.  I try to convey an optimism and enthusiasm for what we are trying to achieve. I try to discourage free riding and I try to celebrate effort and public goods provision. 

I keep thinking back to my undergraduate education and I ask myself; what events would I have learned from if I had had these opportunities 30 years ago?  Based on my memories of my past, I keep trying to schedule meaningful (and fun) events.





Scarce Inputs and Scaling Up Programs Judged to be Effective by RCTs

2017-11-26T14:37:53.743-08:00

This new NBER paper looks quite interesting.  Suppose that I am an inventor and I create a blood test that correctly detects your probability of having cancer .5 years from now.  For my test to accurately predict your future risk probability, a trained nurse must administer the blood sampling.   As I debut my product, I will make sure that the qualified nurse does the test.    The Scaling up problem is that if my test starts to sell by the millions, its accuracy will decline because there aren't enough qualified nurses to administer my test.

So, this isn't a case of constant returns to scale.  As my production rises, the quality of my product declines and the RCT economists would say that my pilot study's average treatment effect over-states the average treatment effect as I scale up the size of my market.

But is this true?   In a rational expectations model, If I can pre-commit that my product will be "big" (both in scale and with regards to its benefits if administered by a well trained nurse), then young nurses will train to be experts in my technology and will obtain the human capital necessary to operate my product. In this case, diminishing returns to my product may not kick in.  I cannot credible signal my future success then a co-ordination failure will occur and the empirical researcher will observe that the average treatment effect declines with my scale of production (because I can't find qualified nurses to administer it).

Alternatively, suppose that I only roll out my product in California.  High quality nurses may start to move to California because they can work with my technology and deliver results. In this case, my product's average treatment effect will not decline with the scale of my sales.

So, when there is a complementarity between a treatment (such as my blood test) and human skills --- the key issue for scale up is "rational expectations and market size"  or "migration and general equilibrium". 

Scarce inputs will not remain scarce for long if we receive a "heads up" of rising demand (i.e high nurse earnings for skilled nurses) or high demand in given spatial location (i.e nurse salaries for high skilled nurses in California).  As usual, the shape of the supply curve in the long run versus the short run plays the key role here.   RCT results can be scaled up if the complementary input is elastically supplied.  If it isn't then you must ask, why isn't it?  What is the barrier to entry?

Note that this is a blog post. I am ignoring "essential heterogeneity" of those at risk to be treated. Instead, I am focusing on the endogenous determination of the treatment's quality (not the demander's response to this treatment).  #supplymatters



Austrian Empirical Economics?

2017-11-23T09:19:53.008-08:00

Sherwin Rosen was one of the greatest University of Chicago economists.  While he did not win a Nobel Prize (he died at age 62 during the year when he was the President of the American Economic Association), his student Richard Thaler won the Nobel Prize and his student Kevin Murphy has won multiple major economics honors.   I was not his best student but he continues to teach me new lessons about economics.   I just read his 1997 paper on Austrian Economics.  I now see that my Climatopolis work is a type of Austrian Economics. My 2010 book (see the short version here) argues that the combination of rising urbanization, human capital and innovation together will allow us to adapt to climate change.  Cities compete for the skilled and those cities that successfully adapt to the challenge of climate change will gain in human capital.  Home prices (and thus income effects) will fall in areas that fail to adapt.  This competition and the potential for migration creates a more overall resilient economy. While I cannot tell you today which cities will win this competition, I am very confident in this "Austrian" vision.At the same time that I continue this work, there are plenty of NBER environmental economics researchers estimating reduced form single equation models of the general form:economic outcome =  a + b*climate conditions +  Ufor example, the outcome variable might be mortality, or worker productivity and the key explanatory variable might be annual days of the year that the temperature is over 100 degrees.Researchers seek out "credible research" designs to estimate "b".  This slope represents the current marginal effect of climate on an economic outcome.  This research ignores cross-elasticities.  If the climate is bad in Kansas but great in Oklahoma and expected to remain so,  the negative shock to Kansas will actually create a boom in Oklahoma.  This is a migration (zero sum game) effect.Yes, a migration cost must be paid but this is a 2nd order effect.Given my read of Sherwin Rosen's paper, I now see that Austrian Economics focuses on the evolution of the economic system.  Entrepreneurs intuit that there is emerging demand for this product (think of Uber) and begin the experimentation to develop it.  Some succeed and some fail.  The system evolves to economize on scarce resources (signaled by prices) that may becoming increasingly scarce.What can NBER's empiricists actually do here to satisfy an Austrian economist's vision?  One empirical agenda is to study emerging venture capital fund investments. Another would be to study patenting behavior in key sectors affected by climate change.   Investment under Knightian uncertainty is an under-researched topic. In this case, firms know that they do not know the future for certain but they foresee certain emerging trends such as increased drought conditions in the American West. Rather than being passive victims, some firms see this as an opportunity and this starts the endogenous R&D progress.Note that the empirical researcher who assumes she is studying a stationary process will begin to observe that the "b" coefficient defined above converges to zero over time (perhaps not in a linear fashion) as lumpy new innovations are developed and brought to market.  This point is one of our key points in this 2017 paper.[...]



Can an Economist "Commune" with Nature?

2017-11-12T13:35:42.185-08:00

Here are two photos I took of our new neighbor.


(image)

(image)



Good Neighbors vs. Yard Rage: A Test of the Coase Theorem

2017-11-11T10:25:45.879-08:00

The NY Times challenges the Coase Theorem today without ever mentioning Coase.  Several examples are given of "neighbors going to war against each other" over low stakes stuff.   To an economist, the puzzle here is why isn't there more "peace and love"?  The fight didn't have to occur. Instead, they should have traded with each other.  Let me set up an example and let's think this through. 

You and I are neighbors and I use a leaf blower on Saturdays that makes you nuts.  You suffer $80 of pain each time I use it when you are home.  I would suffer $50 a week in "pain" if my lawn is filled with leaves.  Given that we are neighbors and can easily communicate and you know that I have the right to use my leaf blower and you know that I"m the cause of the noise, we can solve this issue by trading.  Suppose you give me $30 each week and in return I make sure to only use my leaf blower when you aren't home.  Both of us are made better off by this "trade".

Of course, you would prefer not to pay me but nothing is free.  Why don't these offers occur more often?

Another example is the famous fight between Bono and Billy Squier.    Note that my solution involves no lawyers, no broken ribs and no laws.  Yes, there is a mutual agreement on who has the "property rights" .   When you enter a Starbucks, the buyer of a cup of coffee knows that he does not have  a right to a cup of coffee.     What is the difference between local noise pollution and a cup of coffee?

As Coase knew, much of the modern economy is actually a fight over who actually has the initial property rights. If we could all commit to a common agreement over who owns what and never renege on this deal, our society would be much richer.






Ranking Economists

2017-11-05T17:32:50.963-08:00

This report card suggests that I need to invest more time in the quality of my Ph.D. students.You can also obtain rankings of top institutions and economists in the regions of your affiliated institution(s):United States (you rank 203 of 10448, top 2%)California (United States) (you rank 36 of 1080, top 4%)Pacific States (United States) (you rank 37 of 1280, top 3%)These statistics are based on data from 51320 authors. Rankings for the top 5% authors are available here.MethodYour rankPercentile in RePEc (top x%)Your scoreAverage score at affiliation 1% with null score in RePEcAverage Rank Score3371370.63NA0Number of Works697218970.730Number of Distinct Works431115643.760Number of Distinct Works, Weighted by Simple Impact Factor16714729.431159.020Number of Distinct Works, Weighted by Recursive Impact Factor2131699.92164.720Number of Distinct Works, Weighted by Number of Authors4411104.2729.410Number of Distinct Works, Weighted by Number of Authors and Simple Impact Factors22612490.73633.260Number of Distinct Works, Weighted by Number of Authors and Recursive Impact Factors2731366.5390.740Number of Citations66022429975.8316Number of Citations, Discounted by Citation Age4771678.300248.5616Number of Citations, Weighted by Simple Impact Factor619229161.009070.8916Number of Citations, Weighted by Simple Impact Factor, Discounted by Citation Age45511735.920495.0716Number of Citations, Weighted by Recursive Impact Factor66723754.961090.7916Number of Citations, Weighted by Recursive Impact Factor, Discounted by Citation Age5081297.14078.9916Number of Citations, Weighted by Number of Authors56021432.17482.2116Number of Citations, Weighted by Number of Authors, Discounted by Citation Age3951393.77122.6216Number of Citations, Weighted by Number of Authors and Simple Impact Factors567216633.094502.8816Number of Citations, Weighted by Number of Authors and Simple Impact Factors, Discounted by Citation Age3871986.430243.2716Number of Citations, Weighted by Number of Authors and Recursive Impact Factors62922095.12539.6516Number of Citations, Weighted by Number of Authors and Recursive Impact Factors, Discounted by Citation Age4481165.77038.2716h-index38212613.1516Number of Registered Citing Authors60321374475.9120Number of Registered Citing Authors, Weighted by Rank (Max. 1 per Author)62221042.22353.3220Number of Journal Pages41011536489.3414Number of Journal Pages, Weighted by Simple Impact Factor510128025.809761.0214Number of Journal Pages, Weighted by Recursive Impact Factor68523781.621322.8514Number of Journal Pages, Weighted by Number of Authors3141945.08262.2214Number of Journal Pages, Weighted by Number of Authors and Simple Impact Factors474116329.105248.0414Number of Journal Pages, Weighted by Number of Authors and Recursive Impact Factors63722187.54727.0414Number of Abstract Views in RePEc Services over the past 12 months551100931394.780Number of Downloads through RePEc Services over the past 12 months13912171408.744Number of Abstract Views in RePEc Services over the past 12 months, Weighted by Number of Authors6115803637.650Number of Downloads through RePEc Services over the past 12 months, Weighted by Number of Authors11711168175.024Euclidian citation score13003414.16121.4716Strength of students162441665.6146.195Closeness measure in co-authorship network86024.55NA23Betweenness measure in co-authorship network549210.4900NA45Breadth of citations across fields424191.50NA23Average Rank Score (Last 10 Years)1131134.05NA7*: fewer than 5 scores available for this institution.Institution h-index is defined differently from author h-index.Similarly ranked authorsThese peers are ranked around you and are listed in random order:Giovanni Per[...]



Urban Climate Change Adaptation and Local Real Estate Markets

2017-11-05T17:14:47.031-08:00

For those who wonder if a Department Chairman can get some work done, here is the introduction of my new paper that I will present at the Hoover Institution on 11/8/2017.Urban Climate Change Adaptation and Local Real Estate MarketsMatthew E. KahnUniversity of Southern California and NBERIntroductionThe major productivity hubs in the United States are located in coastal areas such as San Francisco, Seattle , New York City and Boston (Hsieh and Moretti 2017).  In each of these areas, a set of high technology firms and high human capital workers have co-agglomerated creating highly productive clusters.   These cities both attract talent and the close physical proximity between these workers and firms causes better matching between workers and firms such that cross-firm learning takes place (Combes et. al 2012, Glaeser 1998,  Rosenthal and Strange 2004).Such coastal productivity centers raises concerns that natural disaster risk and climate change will impose enormous costs for the U.S  because it could disrupt economic activity.  In early September 2017,  Hurricane Harvey shocked the Houston economy and Hurricane Irma significantly damaged Florida. These events highlight how natural disasters can impact real estate capital.  While the science of climate change features many open questions, we have an increased understanding that different geographic regions will face more extreme temperature and rainfall events and that tail risk of severe natural disasters could worsen (see https://www.ipcc.ch/report/ar5/wg1/).The economic consequences of these geographic shocks hinges on how and where we build our cities.  Over decades, we have made durable investments in capital and infrastructure that place millions of people and billions of dollars of capital in areas that could be at increased risk of sea level rise and other challenges posed by climate change (Changnon et. al. 2000, Pielke et. al. 1998, 1999).Zillow’s researchers have made scary predictions about the aggregate capital losses (perhaps $400 billion in Florida alone) that might occur in the year 2100.[1]  This prospective research overlays maps of current coastal assets with different scenarios of future sea level rise.   An emerging climate economics literature studies the historical relationship between geographic places (such as nations or counties) and examines how their economic growth and population growth co-varies with climate conditions (Hsiang 2016). This research has documented a negative correlation between average temperatures (i.e summer heat) and economic growth (Deryugina and Hsiang 2014).    The Lucas Critique teaches us that past historical relationships may not yield good forecasting rules if economic decision makers reoptimize “as the rules of the game change” (Lucas 1976).  While Lucas originally focused on how individuals respond to changes in government policy, this same logic applies in thinking through how individuals respond to changes in climate patterns. Starting with the early work on rational expectations, economists have emphasized that investment patterns are a function of future expectations (Lucas and Prescott 1971).  If investors “know that they do not know” the likelihood of fat tail risks, they will be less likely to make irreversible large sunk investments.  Such rational agents will instead seek a series of less costly investments that offer the option to wait and see how the threat a specific area faces (Bunten and Kahn 2016).  Expectations of changing climate conditions drives investment patterns and these investments facili[...]



Optimism on Climate Change Adaptation: Lessons from Marathon Races

2017-11-04T09:36:38.974-07:00

Michael Greenstone has written an excellent piece about how climate change is likely to affect marathon races and the runners.  While the headline hints at "doom and gloom", the real meat of the article is highly optimistic about our ability to adapt to this outdoor stress.    The piece has a cliched paragraph listing the litany of challenges we will face but the historical record highlights that the death rate from disasters is declining quickly over time and that induced innovation will step up to address several of the challenges that climate change will pose. Let's be clear, this is the Julian Simon vs. Paul Ehlich debate all over again.  Economists, are you with Simon or not?  My 2010 Climatopolis book anticipated these themes.  In late 2016, I sketched my evolving thinking in this PERC piece.  Back, to Dr. Greenstone;Here is a direct optimistic quote:Marathons will be no exception. The organizers of the New York race will probably not want their event to be one where it is difficult, or perhaps even impossible, for people to set their personal best or to lower the world record. So they may want to adapt by moving the marathon to later in the year.At the same time, runners may switch from the New York City Marathon to others held in cooler climates to find the perfect temperature at just the right time of year. Could a Montreal Marathon be among the world’s most prestigious by 2050?Athletic equipment companies will surely develop new technologies to aid adaptation as well. For runners, the breathable mesh and cooling towels of today could easily be traded in for shirts with built-in air-conditioners. Seem far-fetched? They already exist. Indeed, I was one of the authors of a recent study of just how powerful a role technology can play in helping people adapt to warmer temperatures. For example, the rise of air-conditioning has reduced the mortality consequences of extremely hot days in the United States by more than 70 percent since 1960.Marathons and marathon runners appear likely to be able to adapt to climate change with relative ease through changes in when, where and how. [...]



Ecological Economics Makes a Comeback!

2017-10-21T12:35:25.824-07:00

The WSJ has published a great piece highlighting the wonders of free markets.  In the recent past, U.S manufacturers and consumers sent their waste to China.  China took this combination of useful elements and garbage and extracted some reusable materials such as steel.  Recently, China has announced that it will no longer accept such U.S exports of toxic materials.  Why?  Siqi Zheng and I provide an answer in this 2017 JEP paper.   

From the basic laws of supply and demand, given that China no longer demands these materials;  the equilibrium price of these used materials has fallen.  The WSJ discusses how this is creating a boom in the U.S for businesses that can think about to use this "waste".  A key idea in ecological economics is how to transform one sector's output into a productive input.  So, if a restaurant creates used cooking oil from frying food and this cooking oil can be used by a car to power it , then this is a closed loop ecological cycle. 

The article in the WSJ goes on to discuss the capital investments that the new U.S firms will need to make to effectively use the cheap recycled material as inputs in their production process. I view this piece to be highly optimistic about the nimbleness of the U.S economy in the face of changing market conditions. 



The Value of Structural Econometrics: The Case of China's One Child Policy

2017-10-19T07:21:08.269-07:00

Science Magazine has published an interesting blurb about a Demography piece that claims that China's One Child Policy reduced this nation's total population by a billion people.   How?  The piece claims that by the year 2060 that there would have been an extra billion people in China in the absence of the policy!   We all agree that it is crucial to measure the causal effects of this policy but how does one do this?

There is a fundamental missing data problem.  For every woman in China during the years when the policy was in place, how many children would she have had in the absence of this constraint?  If she would have had the same number of children then the policy wasn't binding!

By estimating a structural econometrics model, one can conduct such a policy counter-factual.  Hilary Clinton only had one child.  My wife only has one child.  Some women choose to have only 1 child (even without a government restriction).

Facts:

1.  women's wages rise with education and among the highly educated,  people with STEM and quantitative degrees earn more
2.  A child's quality is an increasing function of the time that parents spend with the child.  This time effect is diluted if the parent has multiple children.
3. urbanites urban higher wages than rural people
4.  Chinese apartments in cities are highly expensive and an extra bedroom is extremely costly.

These 4 facts yield several predictions;

For the most educated urban women in China, the government's policy is less likely to bind.  For those who value child quality (having the next Einstein), the government's policy is less likely to bind.  So, this policy was really binding for farmers.  Middle class people who are urbanized are unlikely to be able to afford to have a second child.  Why?  The woman would sacrifice too much urban labor income and their rent for the two bedroom apartment would be too high.

As China's urbanization and educational attainment accelerated, the one child policy becomes less and less binding as more women aspire to be the Chinese version of Hilary Clinton.

A structural model would take a formal stand on a woman's utility function (defined over private consumption, quantity of children and quality of children) and would take an explicit stand on the production function of child quality as a function of market inputs and parental time.   By living in a city, the same person has a higher wage (and thus a higher opportunity cost of having a child) and will face higher rents for an extra bedroom.  The researcher would solve for the optimal fertility with and without the one child policy constraint. This constraint states that the family cannot have more than 1 child but if the optimal fertility is 1 child then the policy isn't binding.

My claim is that education and urbanization rise in China, this is not a binding constraint. There would not be an extra billion people in China without this policy.

For some formal academic research on fertility read these.




Amazon Recruiters Visit USC Economics

2017-10-17T14:27:21.009-07:00

I am very pleased to welcome Amazon's recruiters to USC Economics.  Our talented graduate students are eager to speak to this amazing firm.   I just bought a book by Eli Broad on Amazon last night.  Our department's effort to raise the quality of our program is paying off!



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The Costs of Paying for "Performance": The Case of Chinese Universities

2017-10-14T07:39:14.320-07:00

The NY Times has published an excellent piece on the unintended consequences of pay for performance incentives introduced at Chinese universities.  This type of "Freakonomics" highlights several issues in modern economics.   Back in 2000, Ed Lazear wrote a clean AER paper  where he studies how productivity changes at a windshield replacement firm when it switches over to "pay for performance".  He finds that workers work harder when their compensation is tied to "output" rather than to how many hours have passed (i.e a fixed wage per hour).

In the case of research, what is "output"?  As the NY Times article highlights, China's universities have introduced a $ pay bonus system such that publications in top tier journals (think of Nature or Science) yield huge % increases in pay.  This bonus system leads young scientists to devote more effort but the Times article focuses on a second dimension of effort.  The Times argues that this incentive system contributes to cheating through faking data.

The Times article goes on to say that another problem in the Chinese system is that the universities do not have Deans who can judge excellent work. In this case, the journal editors are the judges and the journal editors can be tricked by forged data.  This issue arises in academic economics.  The senior faculty determine who is promoted in a department. If the senior faculty can "read the papers", then the journal names where the papers are published matters less because the senior faculty has the confidence to make up their own minds about the quality of the work. In contrast, if the senior faculty are insecure and don't know a field of scholarship then they will simply "count papers" weighted by the prestige of the journals where they are published.

Everyone knows that it is easier to count output than to judge its quality. In the case of Lazear's windshields, the variation in quality is small because a machine makes the windshields and then duded glue them in to the car. In the case of academia, the variance of output quality is huge. 

Competition across universities in terms of seeking to rise in the national rankings will reward those schools who show "good judgment".

In standard Principal/agent models, the agent chooses her "effort" level and effort is costly but you can imagine models that distinguish between productive effort (learning new math techniques) versus socially unproductive effort (i.e cheating).  How does the principal design a contract to encourage the former and to discourage the latter?

The Holmstrom and Milgrom (1991) model is relevant here.





The Challenge of Phasing Out Coal: Compensating Capital but not Labor

2017-10-13T13:55:27.386-07:00

Michael Bloomberg understands the Coase Theorem.  He has proposed to buy and then shut down some coal fired power plants.   Read Haarstad's 2012 JPE paper on this general topic of environmentalists purchasing coal and leaving it in the ground.  Note that this approach isn't a takings. The coal interests have the property right to use their coal but choose to sell this right. 

But, what about the coal miners and their communities?  Who is compensating them for giving up their life and traditions?  Can they easily transition and become "green jobs" workers?  Unfortunately, I do not think so.  Eyer and I discuss these points in this 2017 paper.  Such a "takings" from these workers is one cause of the Trump coalition. 



What Does an Economics Department Chair Do All Day Long?

2017-10-08T21:05:26.587-07:00

I have now completed my first two months as the Chair of USC Economics.   It is my impression that the University of Southern California fascinates outsiders.  People know that Los Angeles is a wonderful sunny city. People know that USC is a private university raising a large amount of money.  People know that there are very few strong private universities west of the Mississippi.    USC is catching up with its main rival (UCLA) and seeks to be "Stanford South".  The Football team is ranked #14 and the Economics Department is ranked #20 on Repec.Given these points, what do I do?   I read and respond to a lot of email and I attend many meetings.  USC Economics is the largest major on campus.  I am working hard to improve our major. Some of our majors love economics while others like economics. I want to have a flexible (and challenging) major that pushes our most ambitious students while still delivering for the median student.  We are developing our network with our alumni to help place our students in great internships and jobs.   We are fleshing out offerings in computer science, economics writing, public speaking and applied econometrics to help push our students where they want to go while providing them with the rigorous tools that economics can deliver.   Our MA program is large and we are investing to upgrade it.  A leading econometrician from Netflix will be teaching a class for us in the Spring. We are inviting in leading experts to present public lectures.Our PHD program has traditionally been strong in econometrics, development and experimental economics.  We seek to build on this strength by broadening into environmental economics, macro/finance and political economy.   A serious PHD program both trains students well and helps them to land high quality jobs.   We will attract better students if we can deliver on this front.   We are restructuring our PHD program to improve the mentoring and the students' transition to doing independent research.The Chairman not only works to improve the educational mission but also engages in fundraising and faculty recruiting.  As Los Angeles and USC both become increasingly desirable areas to live and work, more prominent economists are hinting to me that they want to join us in the sun.   While I would love to grow our faculty from the current size of 28 to 82, the Deans place some limits on our growth. I spend a fair bit of time talking to our Deans about our growth plan and how we will finance this growth.    We will be hiring 3 new professors this year. Our department is growing and this improves morale. One worry of mine is our physical location.   To maximize the intellectual synergies between the various economics units on campus, we seek to co-locate with the Marshall School in the middle of campus. For historical reasons, the Economics Department has been banished to the periphery of campus (close to a Taco Bell).   For us to maximize our potential and to build up Economics at USC to the level it has achieved at Stanford and UChicago, we need to move to the middle of campus.I spend my time building up the internal quality of our department and engaging in outreach with successful friends of my department and by connecting with other units on campus.  There are many meetings because we have so much potent[...]



A Few Thoughts About Puerto Rico and "Climate Refugees"

2017-10-01T17:48:25.220-07:00

Could a silver lining of the damage caused by Hurricane Maria be that migration from Puerto Rico to more productive places in the continental U.S accelerates?   While the popular media is discussing the challenge caused by "climate refugees", I have argued in the past that migrants are self interested and will look to market signals of real wages to identify which areas will value attracting them.   Here is a piece I wrote about "climate refugees" in May 2016.  Here is another one I wrote in 2014.  As migrants move to more productive places, their families will benefit and they will enrich the areas they move to by increasing the demand for local housing and by giving local employers more workers to choose among.  Yes, incumbents will face more competition for rents and wages but these general equilibrium effects are unlikely to be large.

For those who prefer to read peer reviewed economics articles (rather than blog posts), I recommend Harold Uhlig's 2011 piece about East Germany. He writes   "In this paper, I have documented the ongoing exodus from rural East Germany, especially among the young population. I have documented that wages there remain low and unemployment high, despite levels of education and training that are on par with Western Germany. To understand these facts, one must seek a model which allows agents to improve their situation by migration while at the same time keeping unemployment higher in the sending region."

In the case of Puerto Rico, social networks have anchored many people to remain in this area but these individuals are likely to have a brighter economic future if they migrate to the continental U.S.  While this transition will impose costs, it will improve their children's education and opportunities.  Many parts of the continental U.S feature low home prices and need young people to move there. There would appear to be gains to trade in the local labor markets. So, I do not foresee a "refugee crisis"?  Instead, I see a silver lining from a very painful shock.





Sane Discussion of Disaster Adaptation in the NY Times

2017-09-30T10:55:16.329-07:00

Here is a very nice article  on the "small ball" of building up resilience to climate change.   The interesting empirical question is what % of home owners will be as reasonable as Michele Nilsen?   Since 2010, I have been arguing that this is how we will adapt.  Climate change adaptation offers "the test" of rational expectations vs. behavioral economics theories.   To read my thoughts on these issues, here are a few of my recent papers; Bunten, Devin & Kahn, Matthew E., 2017. "Optimal real estate capital durability and localized climate change disaster risk," Journal of Housing Economics, Elsevier, vol. 36(C), pages 1-7. Matthew E. Kahn, 2017. "Will Climate Change Cause Enormous Social Costs for Poor Asian Cities?," Asian Development Review, MIT Press, vol. 34(2), pages 229-248, September. Matthew E. Kahn, 2016. "The Climate Change Adaptation Literature," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 10(1), pages 166-178. Kahn Matthew E., 2015. "Climate Change Adaptation Will Offer a Sharp Test of the Claims of Behavioral Economics," The Economists' Voice, De Gruyter, vol. 12(1), pages 25-30, August Kahn, Matthew E., 2015. "Climate Change Adaptation: Lessons from Urban Economics," Strategic Behavior and the Environment, now publishers, vol. 5(1), pages 1-30, June.Matthew E. Kahn & Daxuan Zhao, 2017. "The Impact of Climate Change Skepticism on Adaptation in a Market Economy," NBER Working Papers23155, National Bureau of Economic Research, Inc.[...]