Geographical Persistence. Econ 2840

Transcription

1 Geographical Persistence Econ 2840

2 Davis and Weinstein Central question in economic geography: how to explain the distribution of economic activity across space Three principal theoretical approaches: 1 increasing returns 2 random growth 3 locational fundamentals Goal of the paper is to evaluate Much of the emphasis in the paper will be geographic persistence and its implications

3 Increasing Returns There exist advantages of agglomeration spillovers, market size eects, low transport costs to allow for specialization, etc. There are also limits to agglomeration transport of land-dependent stu (food) congestion costs Equilibrium will have some distribution of agglomerated areas Interesting things that can happen: multiple equilibria path dependence catastrophes (in the mathematical sense of abrubt changes in equilibrium in response to small changes in fundamentals)

4 Random Growth Focus on the distribution of size of cities Shows this can arise from simple stochastic process The two big laws Gibrat's Law: Growth of city size is not a function of city size (i.e. regress growth rate on level and get zero) Zipf's Law for Cities: if you regress ln(rank) on ln(size), you get coecient of -1 Gabaix (1999) shows that Zipf's law results from the operation of Gibrat's law

5 Zipf's Law

6 Locational Fundamentals Some places better than others They take the view that what is good doesn't change much, at least after the stone age.

7 Davis and Weinstein Paper examines Japan Two relatively disjoint parts Part 1 looks at regions (most Zipf literature looks at cities) over very long historical periods. 45 prefectures, 8,000 years of data Part 2 looks at cities, with the shock of WWII destruction. Other than the fact that they are both in Japan, there is really no link between these two empirical sections

8 Prefectures measure will be population density My view: conventionally measured density is stupid. Should always use some sort of quality adjusted density. up to the year 300 AD, their measure is density of archeological sites. From 725 onward, source of data is population counts from censuses that provided the basis for taxation. Historical provinces mapped into current prefectures. See Tables... relative variance is variance of log density in year t divided by variance of log density today.

9 Principal Features of Historical Economies (1/2)

10 Principal Features of Historical Economis (2/2)

11 Stu to See in Table 1 Note that population increases 1,000-fold over this data! Even starting in 725 with good census information, population increases 30 fold! relative variation in pop density very high and correlation with present are very low for rst few observations this was stone age / primitive agricultural technology, with most of the country barely habitable. Starting in 725: so why is it in the paper? high (and rising) correlation with present distribution interruption after 1600: share of largest and relative variance decline until end of 19th century This is Japan's cutting o contact with ROW. 8 of the 12 most dense regions in 1600 were ports. share of largest 5 regions and variance of population density only take o in 20th century (surprisingly late).

12 Stu in Table 1 continued Table also shows Zipf coecient Zipf's law is usually applied to cities, so I don't really see why doing this. Regress rank on population density (usual Zipf RHS variable is pop size!) Historical population measured with error attenuation bias. solution: instrument with density in 1998 Story from coecient: large absolute values in pre-20th century period This says a small change in population produces a big change in rank i.e. there is not much dispersion in densities. big drop in absolute value in 20th century moving toward more variance in density. D&W are super-impressed with the strong persistence in density rankings of regions. Am I?

13 D&W Part 2: Bombing of Japanese Cities If persistence is due to agglomeration / infrastructure / coordination then wiping the slate clean would lead to a dierent spatial distribution. If persistence is due to locatinal fundamentals, then this would not be true. US bombing of Japanese cities provides a natural experiment to test. will a temporary shock (bombing) lead to a permanent change in spatial equilibium? Measure of shock: dead and missing relative to 1940 population also data on regionally targeted reconstruction funds, but these are small

14 Bombings 66 targetted cities destroyed 2.2 million buildings half of all structures, 2/3 of productive capacity 300,000 killed; 40% of population (of targeted cities) rendered homeless wooden construction: technology of rebombing perfected over time plus atomic bombs.

15 Variation Among Cities D&W data are 300 cities, 80% of which (37% of urban population) were virtually untouched by bombings. Some big cities not bombed either because of geography / topography (hard to reach) luck w.r.t. weather (Kitakyushu was primary target for Nagasaki bomb) other random factors special case of Kyoto (fth largest city): fear that destruction would stien resolve of Japanese

16 Temporary Shock Bombing over short period of time in Only lasting eects were lingering radiation in Hiroshima and Nagasaki this should bias in favor of nding lasting eects of temporary shock

17 Eects of Bombing on Cities with more than 30,000 Inhabitants

18 Test of Persistence of Shocks Random growth model: shocks are fully persistent test: regress growth after bombing with growth in random growth says zero coecient location specic model says negative coecient shocks are undone (like mean reversion). Instrument for growth with deaths and buildings destroyed note: buildings destroyed aected populaltion much more than deaths.

19 First Stage

20 Two-Stage Least-Squares Estimates of Impact of Bombing on Cities

21 Potential Objection Most declinein population due to refugees rather than deaths deaths/capita averaged 1% in the 144 cities with positive casualties; by contrast change in ln(pop) is in Figure 1 is much higher for bombed cities. Maybe the nding is just people moving back home social networks, place they are familiar with, etc. that would partially undermine the locational fundamentals view in favor of some sort of focal equilibrium view. Atomic bombings: these had much higher ratio of deaths/residents compared to others Hiroshima: 20% Nagasaki 8.5% These cities could not have recovered their populations without new people moving in remeber eect from lingering radiation gives downward bias Also these were not special cities as of 1940: 8th and 12th largest cities, with similar ones nearby

22 Population Growth

23 Match between theories and predictions

24 Davis and Weinstein Bottom Line Since regional variation long pre-dates the forces leading to increasing returns / agglomeration (urbanization, industrialization, low transport costs), this suggests that another set of forces (locational fundamentals) must be at work. rise in concentation after 1900 is indeed due to increasing returns / agglomeration Why doesn't change in nature of production technology lead to shift in which locations are dense? same locational fundamentals still valuable (i.e. being near river for climate, then trade) or path dependence (QWERTY, etc.) The fact that bombing does not change the spaital pattern suggests to them that fundamentals are very important. casts doubt on the real-world importance of catastrophes (in the mathematical sense) (I am half convinced).

25 D&W Bottom Line - continued They believe a hybrid theory in which fundamentals account for spatial pattern of density, but IR aects the degree of spatial dierentiation. implies: when density collapses to a single city, it will be in the best place (I'm skeptical)

26 Left Over from Davis and Weinstein They manage to support the geographical fundamentals view without ever looking at geographic data this is a good direction for research (see my work with Henderson, Squires, and Storeygard). In particular, it would be easy to do an adjustment to density to account for land quality

27 Bleakley and Lin: Portage and Path Dependence The fall line is the last set of falls or rapids experienced on a river before it empties into the ocean The feature is particularly pronounced in the US southeast In early development, fall line was the limit of travel for ocean going ships, and thus a natural location for trans-shipment and markets In early industrialization, falls provided power for mills None of this has mattered for 100 years! Geographic advantage made obsolete this is a dierent natural experiment than Davis and Weinstein

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29 Population Density in 2000 along Fall Line Rivers

30 Many big US cities are at fall line or at portage locations Washington, Richmond, Chicago, Sacramento, Albany, Louisville, etc. Cities on fall line do not growth more slowly than others (that presumably have not lost their natural advantages) This contradicts the Davis and Weinstein view of persistent natural advantages. Bleakley and Lin: natural advantages overcome indeterminacy associated with increasing returns In Europe, places with the suxes ford in English furt in German

31 Other Examples of Geographic Persistence City locations (e.g. Mexico City) New England colleges National borders Ghost Countries (Pritchett, 2006, Boom Towns and Ghost Countries)

32 A Stylized Model from Bleakley and Lin, who adapt it from Helpman V is indirect utility for marginal family moving to a specic location, as function of existing density in location V is reservation utility available at other locations Locations 1 and 2 dier in value of geographic feature (i.e. portage) Heavy line shows indirect utility after geographic advantage has become obsolete

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35 Implications of the Model Case A: when geographic advantage becomes obsolete, densities in two locations will converge this may be slow, due to legacy capital, infrastructure, etc. along the transition, location 1 will have oversupply of that stu also maybe slow because of political considerations (US states, Canadian Maratime provinces) Case B: when geographic advantage becomes obsolete, still end up with dierent densities existing capital as coordinating device could even end up with 1 being the dense location if 2 has a natural advantage historically determined inecient equilibrium (Williams College).

36 Henderson, Squires, Storeygard, and Weil not yet written paper relate lights to rst nature geographic characteristics as well as historical locations of cities, trade routes, etc. Data at one-quarter degree (longitude / latitude) level Questions: how much of the spatial variation in activity is due to geography? how much is due to history? radiance2006 is sum of all lights max=720,391 ; mean=593; sd=6427; skewness=34.6; 36% of observations non-zero. depednent variable: logadjradiance = ln(radiance2006/landarea + 1/777) mean= -4.05; sd=3.68

37 First Nature

38 Coasts and (Natural) Harbors This is test of Sachs view of importance of coasts / trade We use US Navy data on natural harbors

39 Intensive and Extensive Margins Our transformed dependent variable is approximately normal when we restrict to lit grid cells

40 Old World vs. New World There should be a good map to go with this, showing US tted values from New World regression vs. tted values from Old World regression. However, the initial version of this was a big mess.

41 Historical (1500) City Locations % lit is really percentage of observations where the dummy for historical city takes a value of one.