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Immigration, Capital Flows, and Housing Prices Pavlov, Andrey; Somerville, Tsur Oct 6, 2017

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Immigration, Capital Flows, and HousingPricesAndrey PavlovA Tsur SomervilleBASimon Fraser UniversityBUniversity of British ColumbiaAbstractResearch on immigration and house prices has found that immigrants raise metropoli-tan area house price levels, but lower them in immigrant destination neighbour-hoods. In this paper we find that this latter result is not globally true. Ratherneighbourhood house prices can respond positively to immigrant volumes, at leastfor the subset of immigrants studied here, which are those who come with wealth.The contrast with existing work highlights the importance of capital flows, in addi-tion to people, in the effect of immigration on local asset markets. Unlike previouswork that relies on panel data, we exploit a surprise suspension and subsequentclosure of a popular investor immigration program in Canada to assess the impactof wealthy immigrants on local real estate markets using a difference-in-differencesmethodology. Using transaction data from the Greater Vancouver area, we findthat the unexpected suspension of the program had a negative impact on houseprices of three percent in the neighbourhoods and market segments most likely tobe favoured by the investor immigrants. The negative impact of the suspension oc-curred quickly, within the first three months following the policy change. This speedsuggests it resulted from declines in seller expectations and demand by builders toredevelop existing properties into newer more luxurious housing homes. The pricedeclines are larger for more expensive houses in the target neighbourhoods and forneighbourhoods where the share of recent Chinese immigrants among the popula-tion is highest. None of our findings hold for property types not likely to be favouredby investor immigrants, nor for immigrant neighbourhoods favoured by those un-likely to be investor immigrants. Adding our findings to the existing literature onimmigration and housing markets makes it clear that immigrants can have posi-tive effects on local housing prices, but the effects depend on who the immigrantsactually are and highlights the role of capital in augmenting immigrant demand.Key words: Real Estate Demand Shocks, Immigration, Real Estate Valuation1 We gratefully acknowledge BC Assessment’s assistance in providing transaction and property characteristicsdata for this paper.1 IntroductionImmigration has become a highly charged political topic as large refugee flows in Europeand the desire to control borders in other developed nations has led to the rise of sup-port for nativist and nationalist polices by select governments and parties in Australasia,Europe, and North America. And while much of the anxiety about the impact of popu-lation flows has focused on the effects on cultural norms, labour makrets, and security,at the local level there are housing market effects from immigration driven demand.At the same time, international capital flows (foreign investment) has been blamed forexacerbating, or by some causing, severe problems with housing affordability in citiessuch as Hong Kong, London, Melbourne, New York, San Francisco, Seattle, Singapore,Sydney, Toronto, and Vancouver. 2 While the attention in the press has been on non-resident buyers, capital can come with people as well: Australia, France, Germany, theUK, and the US, among others, have visa programs that provide residency to those withwealth who invest a proscribed amount in the local economy. In this paper we studythe relationship between wealth, immigration, and local housing markets by examiningthe changes in programs for this type of wealthy immigrant. Our results show that thepackaging of people and capital raises house prices in destination neighbourhoods, sothat if there is in fact any native flight, this is more than offset by immigrant demandfor housing.In response, countries such as Singapore and the UK have recently taken steps to limitforeign investment through restrictions on purchases and higher taxes on non-residentbuyers. 3To identify the effects of wealthy immigrants on local housing markets, we exploit thesurprise suspension and subsequent closure of Canada’s investor immigration program. 4Unlike previous work, which uses panel data, the sudden termination of the Canadianinvestor immigrant program allows us to treat this as a quasi-experiment and use adifference-in-differences methodology to identify the effects of immigrants, or at leastthis class of immigrants, on neighbourhood house prices. Using transaction data from2 South China Morning Post 3/13/13; Credit Suisse 3/4/14; www.sfgate.com 11/29/14;New York Times 2/7/15; Globe and Mail 4/20/15; Evening Standard 10/21/15;www.bloomberg.com 11/2/15.3 For example, in the UK the government imposed capital gains taxes on foreign ownersof residential real estate, reduced the threshold for higher stamp duty rates, and appliedthem to homes owned through companies.4 The program has since been reopened the program, but with the number of applicantsnationally for 2015 limited to 120, as compared with over 10,000 accepted per yearduring the height of the program2Vancouver BC, the largest single destination in Canada for investor class immigrants,we compare within metropolitan area house price appreciation between census tractsthat were likely destinations for investor immigrants to those that were not. The periodof analysis is the short window immediately preceding and following the July 2012announcement of the program suspension. We compare the effect of this shock on thechange in house prices in likely investor immigrant census tracts as compared to changeover the same period house prices in census tracts unlikely to be destinations for theseimmigrants. Because the effect of people is not separate from that of capital in our targetpopulation, our contribution to the policy debate on the effects of foreign capital aloneon local housing markets is somewhat limited. But, we unambiguously demonstrate thatsome classes of immigrants can cause neighbourhood house prices to rise.Our main finding is that immigrant flows can raise local house prices is in clear con-trast to previous work such as Saiz and Wachter (2011) and Sa(2015) who found thatnative flight dominates immigrant demand resulting in lower house prices in immi-grant destination neighbourhoods. Specifically, the results in this paper show that inthe year following the suspension of the immigrant investor program, house apprecia-tion in neighbourhoods with high concentration of recent Chinese immigrants laggedother neighbourhoods in the Vancouver metropolitan area by 2.3 percent. The houseprice appreciation underperformance starts in the month following the announcement,and extends over the following 12 months. The effect dissipates for longer periods. Thisdissipation does not appear to be because the drop in demand is then spread to otherareas, but rather because house prices in the wealthy immigrant investor destinationcensus tracts recover. The net positive effect on house prices of wealthy immigrant de-mand requires that local residents do not choose to segregate themselves from wealthyimmigrants in substantial enough numbers to offset the positive effect on neighbourhoodprices from the demand effect of the inflow of households with high levels of wealth.We believe that the difference between our findings and those in the existing literatureon the effect of immigrants reflects the difference between our subject group of wealthyimmigrants and the more commonly studied groups of less fortunate and lower humancapital immigrants where their demand is not sufficient to offset native flight, and wherethe latter may be larger in magnitude than in our case.Our results are robust to various model specifications and variable definitions. We docu-ment no differential across the program suspension on sub-market segments not favouredby investor immigrants. These include destination census tracts for immigrants unlikelyto be investors, condominium units, and census tracts with lower valued housing. Forboth of the latter we treat these as sub-markets that would be less likely to be purchasedby households with the considerable wealth necessary to qualify for investor immigrantstatus. Our approach requires that certain neighbourhoods (census tracts) be intendeddestination areas for investor immigrants. Unavoidably there is potential bias because”treatment effect” of the program suspension and closure will not be randomly allocatedacross census tracts. We rely on both the short time window and fixed effects for largerneighbourhood classifications to mitigate this bias.3The paper proceeds as follows. Section 2 reviews the existing literature on the impact ofimmigration and capital flows on real estate values. Section 3 identifies the theoreticalissues in the relationship between wealth, immigration and neighbourhood house prices.Section 4 presents and explains the natural experiment. Section 5 describes the dataand variable definitions we use. Section 6 presents the empirical findings, includingrobustness analysis. Section 7 concludes with a summary and suggestions for futureresearch.42 Immigration and Real Estate - BackgroundSaiz and Wachter (2011) point out ”immigration is not so much defined by the consump-tion of foreign labor, which can also be achieved by international trade, internationaloutsourcing, or telecommunications...(as) by the physical presence of immigrants in thehost country.” The primary focus of studies on the economic effects of immigrationhas been on its impact on native born wages, employment and economics growth. Alarge body of research focuses on the labour market effects (early work of note includesCard 1990; Borjas, Freeman, and Katz 1996; Butcher and Card 2001). Papers such asManacorda, Manning, and Wadsworth (2012), Ottaviano and Peri (2012), and Dust-mann, Schonberg, and Stuhler (2017) highlight differential impacts of immigration onvarious labour market segments, a result that echoes with the differences in our find-ings compared to other research on the effect of immigration on house prices. Negativeeffects of immigration on housing require native flight because of a desire to avoid livingnear immigrants or changes to neighbourhood amenities because of immigrant inflow,this too has analogies in other areas of research such as Scheve and Slaughter (2003)and Mayda’s (2006) work on native attitudes towards immigration and Cutler, Glaeser,Vigdor. (2008) on immigrant segregation.The main body of research on immigration and housing markets has studies metropoli-tan area effects, typically through a panel of metro areas or on occasion through timeseries in a single housing market. Burnley and Murphy (1994) find that there are pos-itive links between immigration and house price movements in Sydney, Australia, andBourassa and Hendershott (1995) show that net overseas migration is associated withthe real estate gains in six Australian state capitals. Using the metropolitan area as theunit of analysis, Saiz (2007) finds that immigration flows raise house prices and rents:immigration volumes on the order of one percent of total population raise these 1.0and 2.9-3.4% respectively. Using more aggregate provincial level data in Spain, which isthen disaggregated into multiple within province regions, Gonzalez and Ortega (2013)yield similar magnitude effects for immigration and house prices. A dissenting view isSa (2015) who with a panel of United Kingdom local authorities finds that the sameone percentage point increase in immigrant volumes as a percent of total populationlowers house prices by 1.7 percent. She does find variation across the distribution ofimmigrant education levels, as there relationship is not statistically significant for thelocal authorities with the top quartile of average immigrant education.In contrast to the positive aggregate effects, studies of immigration and house pricesthat have used within metro area variation for identification have found negative rela-tionships between immigrant volumes and house prices. Saiz and Wachter (2011) use ageographic diffusion model to represent the growth of immigrant density of a neighbour-hood. Their main conclusion is that growing immigrant density appears to cause nativeflight and slower appreciation. Ibraimovic and Masiero (2014) find that immigrants toSwitzerland are willing to pay a modest premium to locate near co-nationals. But, asin Saiz and Wachter, native born pay a higher premium to avoid neighbourhoods with5large non-native populations. However, this premium declines with education level andas the immigrants are less ”dis-advantaged.” They do not identify the extent to whichimmigrant preferences for locating with co-nationalists dominate or fail to dominatethe preference of local-born to avoid immigrant neighbourhoods. In a paper looking atcensus tract in Vancouver, Moos and Skaburskis (2010), find the reverse. 5 They com-pare the changes between the 1981 and 2001 Canadian censuses and allow for geographicvariation by disaggregating the Vancouver Census Metropolitan Area (CMA) into 4 dis-tinct areas: inner city, old suburbs, new suburbs, and exurbs. At the census tract levelthe correlation between recent immigrant status and higher dwelling value appreciationis positive over the twenty year period, controlling for other factors such as mediantract income or population. This finding is more noticeable in the inner city and oldsuburbs, than in the new suburbs. Their paper cannot determine causality or whetherimmigrants are attracted to neighbourhoods with higher house price appreciation.Related to these within city studies are longer run studies using census tract data, whichget identification across within city districts. The ten to twenty year samples evaluatedat five year intervals allow for a more elastic supply response than mor cross-sectionalanalysis. Stillman and Mare (2008) and Akbari and Aydede (2012), studying high immi-gration countries of New Zealand and Canada respectively, find small but still positiveeffects of immigration volumes on house price levels, on the order of immigrations vol-umes of one percent of population increasing house prices one percent.Despite this substantial and long-standing effort to estimate the impact of immigrationon real estate, we are not aware of any attempts to use a change in the immigrationpolicies of a country or a region to capture a causal relationship, or to identify thechannel through which such a relationship works. This is understandable, as changesin immigration policies are rare, modest, and/or not surprising. The discontinuationof the immigrant investor program in Canada, and the socio-economic characteristicsof Vancouver, offer a rare opportunity to fill this gap in the literature and allow us toinvestigate the possibility of a direct causal link between immigration and real estatevalues. The nature of immigrant is an important issue. Saiz and Wachter suggest thatimmigrant neighbourhoods may not be becoming relatively less attractive because theyare populated by the foreign born per se, but because they are more likely to con-tain populations with perceived low socioeconomic status. This is consistent with Sa’sfindings that higher education levels among immigrants appears to attenuate negativeeffects of immigrant volumes on house price levels. Our analysis of a change in a pro-gram targeting high net worth immigrants allows us to identify differences in resultsstemming from immigrant type.The Canadian investor immigrant program that we study focused on high net worth5 Immigration is particularly important for growth in aggregate demand in Vancouver.Ley and Tutchener (2001) calculate that immigration to Vancouver contributed 54%to net population growth between 1986 and 1991, and 79% during the first half of the1990s.6individuals and involved the transfer of financial capital as well as the immigrants ownhuman capital. As such, the effects of the capital brought by these immigrants shouldbe similar to those resulting from foreign direct investment in residential real estate.Favilukis, et. al. (2013) review the literature on capital flows and house prices, finding apaucity of clear results. Sa, Towbin, and Wieladek (2014) use a country level panel forOECD countries and a panel VAR approach, finding that capital inflows are positivelyassociated with faster rates of house price appreciation. At the sub-national level, butstill using market level aggregation, Sa (2016) looks at the share of transactions for a lo-cal authority in the UK that are registered to overseas corporations and the relationshipof this measure to house price appreciation. She borrows from Badarinza and Ramado-rai (2015) using their approach to create instruments for foreign investment shares. Inher work, a one percentage point increase in foreign company share of transactions isassociated with 2.1 percent higher house prices. 6A second group of papers study the effects of capital inflows into real estate by exploitingwithin market variation. Liao, et.al. (2015) identify the transmission of shocks to salesto foreigners and price increases in the prices of units sold to local buyers in Singapore,but this effect is small: a one percent increase in the volume of sales to non-residentsresults in a 0.027% increase in prices in the domestic market. The price effects in thenon-resident market are five times as large. They use a time series approach and relyon the separation of the two markets, where few non-residents can buy in the residentmarket. Cvijanovic and Spaenjers (2015) study non-resident demand in Paris. Theyfind capital inflows concentrate in the most desirable neighbourhoods and affect pricesmore generally. Their effects are twice those of Liao, et. al, a one percent increase innon-resident purchases leading to a 0.05% increase in overall Paris prices. Their iden-tification comes from the geography of preferences, where non-resident purchases areconcentrated in particular higher-end districts of Paris. Finally, Badarinza and Ramado-rai (2015) find evidence that risk driven capital flight can explain short-term movementsin London property prices: house prices rise relatively faster in immigrant concentratedneighbourhoods as risk increases in said immigrants’ home country. Their paper takesadvantage of clustering in space by immigrants in different areas of London by ethnic-ity. Both for this reason and because capital and people are likely to flow together intheir study, it is the closest in both subject material and method to our work here.Their variation comes through changes in the desire of people and capital to leave theirhome country, while ours works through changes in whether they are allowed to do so.A connected paper is Suher’s (2016) examination of the introduction of a differentialproperty tax (approximately a 20 percent increase in tax incidence) in New York Cityfor condominium owners whose property is not their primary residence. This is not iden-tical to foreign capital because of domestic investors. He finds a clear effect on extent ofnon-resident ownership, a drop of up to four percent depending on price segment, butno effect on the overall level of prices. However, in areas with significant non-residentownership, prices fell by nearly 10 percent.6 This turns out to be non-trivial. Her counterfactual is if there was no foreign invest-ment, cetris paribus, average house prices would be 19% lower in England and Wales.7The primary contribution of the work in this paper is t highlight that immigration canresult in higher neighbourhood prices. Whether native flight is present is indeterminatein our empirical approach. But if present, in our data immigrant demand effects woulddominate flight. We show this using a quasi-experiment methodology, which gets aroundsome of the causality challenges in the existing work. Our contribution to the literatureon immigration and capital flow is to highlight a number of patterns. First, immigrantneighbourhoods are not necessarily close substitutes for all other areas, as demandshocks are only partly transmitted in a two year period. Second, effects, at least atthe upper end, operate not through native flight, but through changes in demand forhousing and/or expected changes in immigrant buyer demand on the part of sellers anddevelopers83 Immigration, Capital Flows, and House PricesImmigration and capital inflows affect house prices through three channels: increases inaggregate market-wide demand, increases in expected future rents, and preferences forspecific locations (neighbourhood demand). Individual immigrant household demandfor housing reflects immigrant household composition, income, and wealth. In all casesthe effects will depend on citywide and local area supply elasticities, which in turndepend on the extent of regulatory strictness (Mayer and Somerville 2000, Quigley andRaphael 2006, Glaeser and Ward 2009, and Jackson 2016), geographic features anddevelopable land supply (Rose 1989 and Saiz 2010), and the presence of geographicamenities (Davidoff 2008).Both immigration and capital inflows should increase aggregate demand for housingresulting in higher house prices. The first shifts the aggregate demand function to theright because of the increase in the number of households demanding housing. Thesecond is a shift out in demand per household, either because new households arrivewith greater wealth than the existing average household has or non-resident buyers whodemand housing without changing the resident population.A more subtle way immigration and capital inflows can affect current real estate valuesis through the capitalization of future rents into current house prices. This requiresimmigration induced changes in labor supply or capital inflow generated investmentincreases that raise productivity or yield further inflows of labour or capital, all ofwhich would increase future demand for real estate and thus future rents. These higherfuture expected rents will be capitalized today as increases in current real estate prices.As with aggregate demand this is a metropolitan area wide effect.The feature that this paper addresses is the variation in the effect of these inflowsacross neighbourhoods within a metro area housing market because of immigrants orinvestors preferences for distinct neighbourhoods or non-immigrant residents preferencesto avoid living near immigrants. Either can result in changes in the relative price ofhousing across different neighbourhoods in a metropolitan area. The extent to whichdifferential price responses are observed depends on the strength of the preferences andthe cross-elasticity of demand between neighbourhoods. If neighbourhoods are perfectsubstitutes, than any change in wealth and population will affect all neighbourhoodsidentically. In contrast, with perfectly inelastic cross-substitution demand increases inone area, would not change prices in other areas of the city. Card (2001, 2007) finds noevidence of Immigrant displacement or native flight, while Borjas (2006) finds in metroareas about a 60 percent displacement factor.To identify this third effect we use a difference-in-differences empirical methodologyacross census tracts within neighbourhoods. To observe a differential effect betweeninvestor immigrant destination neighbourhoods and others following the change in im-migration policy we need both that immigrants prefer certain neighbourhoods (or locals9have dis-utility from living with immigrants) and then in the aggregate there be ”suffi-cient” cross-neighbourhood inelasticity to observe price effects. If either conditions failthan any effect from the policy change would be the same for all areas and thus not beobservable in our tests.104 Identification and MethodologyThe Vancouver Metropolitan Area offers an excellent location to test the effects of immi-gration on the housing market. Immigrants made up 79% of the change in metropolitanarea population between 2006 and 2011, and 56% between 1986 and 2011. We treatthe suspension of the investor immigrant program as an exogenous shock to expectedfuture immigration to British Columbia (BC). Our methodological approach is a stan-dard difference-in-differences test between neighbourhoods that are the destination forimmigrants most likely to have entered under the investor immigrant program com-pared with those that are less likely to host investor immigrants. Any effect from thissuspension will be concentrated in the Vancouver market as over 95% of the investorimmigrants to BC between 2007 and 2011 settled in the Vancouver metropolitan area.4.1 The Canadian Investor Immigrant ProgramThe investor immigrant program to Canada started in 1986. 7 The program requiredpotential immigrants with a certain minimum net worth to provide money for a five yearterm to the Federal or Quebec government to invest as the government saw fit, with nopromise of interest. The amount started as investment of $C150k for individuals with$C500k of net worth, which was raised to $400k and $800k in 1999 and then to $C800kand $C1.6M in 2010. 8 The actual equity at stake was even lower: Canadian bankswould loan about eighty percent of the funds for an investor, holding the governmentpromissory note as collateral and requiring the remaining twenty percent of funds beheld in their bank. The program is quite inexpensive by international standards. Forinstance, Australia requires a minimum investment of $A4M, approximately $C3.9M.While the US only required a $US500k investment for the EB-5 program, this could notbe financed.The investor immigrant program was closed to new applicants on July 1, 2012 andcompletely eliminated on February 11, 2014. While some applications already in the7 At the same time the Province of Quebec started a similar program. In Canada theFederal Government administers immigration for all provinces and territories, exceptfor Quebec, which administers its own program for economic class migrants. Since 2005provinces and territories are also allowed to nominate their own immigrants under fed-eral guidelines, which accounted for 15 percent of all immigrants in 2013. This focuseson a province’s own areas of economic need.8 Over the period the exchange rate for the Canadian dollar with the US dollar rangedfrom $C 1.00 = $US 0.63 in 2002 to a high of $US 1.04 in 2010.11system were processed following the July, 2012 suspension, it was widely accepted thatthe program had de facto ended.The program has had a relatively small share of total immigration to Canada, but it hasbeen rather more important for BC. From the start in 1986 the number of immigrantsarriving in Canada under the investor immigrant program rose to a peak of 12,624in 1993. This represented 5.4% of all immigrant arrivals that year. The numbers thendeclined to a nadir of 3,695 (1.5%) in 2003 before rising to a peak again in 2010 of11,700 arrivals (4.3 percent of total immigrant arrivals that year). The program hasbeen more significant for British Columbia, and by extension Vancouver since as notedabove nearly all economic class immigrants to BC settle in the Vancouver area. In1993, 6,866 investor immigrants landed in BC. 9 The number dropped to 1,387 in 2000before rising again to peak at 5,870 in 2008. Investor immigrants made up 13.3% ofall immigrants to BC in 2008 and 57.5% of all investor immigrants to Canada in 2008initially settled in BC.4.2 Identification StrategyOur identification strategy rests on a number of factors. First, that the program cancella-tion was a shock. Second, that at a minimum there was an expectation that the programsuspension would affect the future arrival of wealthy Chinese immigrants, whether itdid or not. Third, that immigrants, and in particular those that did and would use thisprogram choose distinct neighbourhoods. Finally, that we can accurately identify theseneighbourhoods.Though its formal closure in February, 2014 was not considered a surprise (the Globeand Mail, February 11, 2014), the initial suspension was. Local immigration expertshave confirmed that nobody in the industry expected the change. It was reported in theCanadian and Asian press as an unexpected move. Many applicants were in the processof preparing their documents when the suspension was announced and the applicationsof those in the pipeline were subsequently terminated. These facts are consistent withtreating the announcement as a surprise.How much the suspension changed the actual flow of wealthy Chinese buyers of Van-couver property is hard to determine. In the immediate aftermath of the suspension,9 This does not include those who landed in another province and then moved to Van-couver. For instance, 36 percent of business class immigrants to Quebec between 2000and 2006 subsequently moved to British Columbia. In comparison only 0.9 percent offamily class immigrants made a similar move. This movement is fairly unique to Quebecinvestor class immigrants another one-third of whom moved to Ontario (Toronto).12investor immigrants who had received their visa continued to arrive but at a sharplydeclining rate. In BC the arrivals fell from 3,860 in 2011 to 2,245 in 2013 to 175 in 2015.What matters for our analysis is that, in addition to the actual drop in immigrants, sell-ers or developers buying existing homes to redevelop for the wealthy immigrant marketalso expected a decline in demand at the time of the program suspension. What we needfor identification is any combination of an actual drop, expected decline, or even justincreased uncertainty regrading future arrivals. Our discussions with local experts con-firms both an immediate decline in distinct mechanisms for high net worth individuals toimmigrate based on their net worth and the uncertainty that were in media reports. 10Wealthier immigrants to Canada from China, typically use immigration consultants inChina to advise them on which programs to use and how to apply. After the suspensionof the Federal Investor Immigrant Program, consultants looked for other mechanismsto facilitate immigration from China to Canada for wealthy clients. Conversations sug-gest that there was a delay in applications as these alternatives were being assessed.The choices seemed to be the Quebec investor program, which had 1,250 slots in 2014,and limits by country, or various options for investors under the provincial nomineeprograms. For instance, after July 2012 applications to the BC provincial nominee busi-ness program went from 100-150 to 1,000. In any case, the loss of the Federal investorprogram resulted in a substantial and clear decline in the number of available visa slotslimited exclusively to wealthy immigrants. While wealthy immigrants are likely to havefound other mechanisms to continue to immigrate to Canada, the suspension and clos-ing of the Federal program removed the number of slots at the federal level exclusivelyavailable to them, disrupted the flow of these immigrants, raised the application andcompliance requirements, substantially extended the process, and, above all, increasedthe uncertainty about the number and time frame for the arrival of wealthy immigrants.There are clear immigrant areas in the Vancouver CMA by country of origin, which willallow us to identify destination neighbourhoods for wealthy immigrants. In 2011 recent(defined as those who had arrived in the past five years) immigrants made up 3.6% orless of the population in 25% of the 454 census tracts in the Vancouver CMA and theirpopulation share exceeded 8.9 percent for the upper quartile. In three tracts, at least22% of the population were recent immigrants. The skewness of the distribution of theproportion of recent immigrants in a tract is 1.11 suggesting significant asymmetry in thedistribution. Within particular immigrant groups, this is skewness is even stronger. Forimmigrants from China, Taiwan, or Hong Kong, 35% of tracts had no recent immigrantsfrom these countries and in 13 of the 454 census tracts recent immigrants from thesecountries made up over 10% of the population. For this group the skewness of thispopulation share is 2.19.Unfortunately, we are not able to explicitly identify tract level variation in recent im-10 The information in this section is a result of conversations with immigration lawyersin Vancouver about the investor immigrant program as well as media reportts at thetime.13migrants by the category for which they obtained a visa. At the census tract level weare restricted to home language and country of origin, and with the latter both for thetotal number of non-native born and those who arrived over the previous five years.We use the dominant presence of immigrants from China and Taiwan in the investorimmigrant program to identify likely investor destinations by immigrant country of ori-gin. Between 2006 to 2011, 24,509 investor immigrants and their dependents landed inBritish Columbia. Of these, 66 percent were from Mainland China and another 15 per-cent from Taiwan. China was the leading home country for immigrants to BC over thisperiod with over 23% of all immigrants to BC arriving from China, and of these 36%came under the investor program. Investors made up 43% of immigrants from Taiwan,but immigrants from Taiwan made up only 4.4% of all immigrants. In contrast, forthe next two largest source countries for immigrants to BC, the Philippines and India(17 and 14% shares of immigration respectively), only 0.6% and 0.4% of immigrantscame in under the investor program. Overall investor immigrants made up only 3%of immigrants from all other countries. Since we use all Chinese immigrants to proxyfor wealthy immigrants, we likely overestimate the volume of wealthy immigrants, thusunderestimating their specific wealth effects. Therefore, that any price effects we findshould considered as a lower bound.The connection between wealth and country of origin shows up in other ways. Chineseimmigrants are more likely to locate in census tracts with higher median house values.The correlation between recent Chinese and Taiwanese immigrants and median tractvalue in 2011 was 0.37, compared with -0.49 for recent non-Chinese immigrants. Thelocal conventional wisdom is that the wealthy immigrants buy primarily single-familyhomes in very specific neighbourhoods for their own use, immediately or in the future,is consistent with these correlations. In other words, while the impact of the immigrantinvestor program over the entire metropolitan area may be modest in terms of bothpopulation and income/wealth growth, the impact of the program in terms of localizedreal estate values is potentially substantial. To put this in perspective, approximately2,200 immigrant investor households can have a very substantial localized impact onthe real estate markets that recorded approximately 20,000 single-family transactionsfor all of 2010.The above facts lend themselves to a natural identification strategy. Since the immi-grant investor program brought in immigrants who had tended to purchase housing inspecific neighbourhoods, we can use the difference in appreciation rates between neigh-bourhoods to measure the impact of the suspension. Specifically, we identify neighbour-hoods with high concentration of recent Chinese immigrants using 2011 Census data.We then estimate a hedonic model of single-family transaction values on various physicalcharacteristics and time-related variables that allow for different appreciation rates forneighbourhoods with high and low concentration of recent Chinese immigrants aroundthe July 2012 suspension date.144.3 MethodologyFor all methods described in the paper, we use semi-log regression models. The variablesin the hedonic pricing model are lot size (logged), living area (logged), age, number ofbedrooms, number of bathrooms, garage, and pool. We include the square of age, lotsize, and living are to capture the non-linear impact of these variables on price. Finally,we model the interaction of time effects and immigrant concentration data using threemodel specifications described below.In our empirical specification, we use the ratio of recent Chinese immigrants (previous5 years) to total population by census tract, as measured by the 2011 census, to captureareas that are desirable to Chinese immigrants.propChinese =(Recent Immigrants from China, 2011)(Total Population, 2011)(1)This is admittedly an imprecise measure as close to 20% of investor immigrants arenot Chinese and 64% of Chinese immigrants enter Canada on programs other than theinvestor program. To address the latter, in the robustness checks below, we examinehigher value homes, which should be more likely to be bought by investor immigrantsthan those who entered by other programs. We also utilize quantile regression methods.The results of these robustness tests are consistent with our more general findings andresult in larger coefficient point estimates.4.4 Statistical Estimation Difference-in-Differences Hedonic ModelWe estimate a hedonic model with a difference-in-differences specification that includesan indicator variables to capture tracts with high concentration of Chinese immigrantsand the interaction of this variable with an indicator variable that captures whether atransaction took place after July, 2012. Specifically, we regress the log price as a functionof the above characteristics, neighbourhood fixed effects, and the Chinese immigrant andpost-July, 2012 indicator variables. The measure of immigrant concentration we use isdefined above by Equation 1. A census tract is defined as ”Chinese” if it has above-median concentration of recent Chinese immigrants. In the empirical section we presentresults for various other cut-off levels used to define a Chinese census tract.log(Price) = β0 + β1Characteristics+ β2∑1(Property in neighbourhood i)+β3Chinese+ β4postJuly2012 + β5Chinese ∗ postJuly2012(2)15We are primarily interested in the parameter β5. A negative parameter would indicatethat prices in ”Chinese” neighbourhoods declined more than otherwise post announce-ment.4.5 Linear Trend AnalysisIn addition to the time dummy variable estimation described above, we employ a lineartrend model to test for a difference in returns between Chinese and non-Chinese tracts:log(Price) = β0 + β1Characteristics+ β2∑1(Property in neighbourhood i)+β3t+ β4t ∗ postJuly2012 + β5t ∗ Chinese+ β6t ∗ Chinese ∗ postJuly2012(3)where t measures time since the beginning of the sample and Chinese is an indicatorvariable for high Chinese immigrant concentration census tracts as defined by Equation1.The model defined by 3 allows for separate linear trends for high- and low-concentrationtracts before and after the announcement. A negative β6 would indicate that the highimmigrant concentration tracts underperformed post announcement.4.6 Concentration Slope AnalysisThe time dummy and linear trend analysis presented so far inevitably depend on theconcentration cut-off levels used to define census tracts with high and low-concentrationof immigrants. As we will point out below, our results are robust to a wide variation ofthese cut-off levels. Nonetheless, in what follows we present an alternative estimate ofthe immigration reform impact that does not require any cut-off level definitions.Specifically, we consider the following model:log(Price) = β0 + β1Characteristics+ β2∑1(Property in neighbourhood i)+β3(Chinese Concentration) + β4postJuly2012 ∗ (Chinese Concentration)(4)The variable of primary interest is β4 which captures the change in the impact ofChinese immigrant concentration post announcement. A negative β4 would indicate that16neighbourhoods with high immigrant concentration underperformed post announcementrelative to their pre-announcement standing.5 Data Sources and Variable DefinitionsThis paper combines data from three different sources. The transaction and propertyattribute data are from British Columbia Assessment (BCA), the province’s tax assess-ment administrator, and include all residential properties and transactions registeredwith British Columbia’s Land Title Office. Census tract data is from Statistics Canada’s2011 National Household Survey, which is similar to the American Community Survey.The third source is immigration data of immigrants to British Columbia by class of im-migrant and source country from Citizenship and Immigration Canada and BC Stats.The individual property data from BCA is geocoded and then matched to census tracts.The data from BCA is the universe of all properties in the Vancouver metropolitan area(Vancouver CMA). All properties are categorized by the primary structure or use of thelot, which for residential uses includes various categories of single detached, attached,town or row-house, and strata lot (condominium) properties. The characteristics datainclude lot size (for single family attached and detached units only), floor area, numberof bedrooms, year built, number of full and part baths, whether the lot has a pool, andthe presence and size of garages. Lot size, garage, and pool data are not available fortownhouse and strata-lot (condo) units. The summary statistics for these variables areshown in Table 1, with detached units in the upper panel and townhouse and condodata in the lower panel.BC Assessment (BCA) provided the universe of transactions and transaction prices forthe period 2010 to 2014. BCA identifies approximately two-thirds of these as qualifiedtransactions for their internal analytic purposes in estimating property market values.According to BCA the unqualified transactions are not arms length or appear to beoutliers in some way based on their internal assessment of price distributions, unitcharacteristics, location, and transaction patterns. We perform the analysis using onlyqualified sales.We apply the following filters to the data:Single family:• Floor area between 1,194 and 4,252 sq. ft., which excludes the top and bottom 5%of the floor area distribution• Lot size between 2,640 and 11,389, which drops the bottom 1% and the top 10% ofthe lot size distribution17• Price between $100,000 and $3,500,000, which excludes the bottom 0.5% and thetop 2% of transactions.Condominium units:• Floor area between 880 and 4,252 sq. ft, which excludes sizes below the median andabove the top 5% of the distribution• Price between $50,000 and $3,500,000, which excludes the top 0.2% of transactionsThe single family filters described above isolate the homes we suspect to be of primaryinterest to investor immigrants. Specifically, immigrants who can afford homes above$3,500,000 and above our size cut-offs would likely still be able to come to Canadaunder the Provincial Nomination Program, and were less affected by the change inthe Investor Immigrant Program. As well, single family transactions are sensitive tothe extreme right hand side-tail. The condominium filters were designed to capturecondominium units relatively comparable to single family homes, although clearly thissample includes much smaller units than even the smallest single family homes.All our results are very highly robust to choice of specific cut-offs. In particular, the lowerprice cut-offs for single family and condominium units can be completely eliminated.The upper cut-offs are important to the extent that it is very difficult to fit a modelto homes that are multiple standard deviations above the median. Using an upper cut-off level of up to $5,000,000, which excludes the upper 0.05% of condo transactionsand the upper 0.6% of single family transactions, does not alter our results. Includingobservations above this does not change the coefficients substantially, but increases thestandard errors for all estimates.Census tract data are the values as reported in 2011 Canadian census or estimatedtract values reported in the 2011 National Household Survey for the Vancouver Cen-sus Metropolitan Area (CMA). 11 We identify immigrant neighbourhoods among the455 census tracts in the Vancouver metro area using the estimated number of recentimmigrants from a given country that arrived in Canada 2006-11. 12 In the case of im-migrants from Mainland China, the mean tract has 80 recent Chinese immigrants out11 The 2011 NHS was the voluntary replacement for the Canadian long form census,the former was sent to thirty percent of households and the latter to twenty percent.The voluntary 2011 NHS is the source of some controversy as participation was notmandatory, unlike the prior long form. Nationally the non-weighted mean non-responserate was 31%, and tended to be higher in lower income tracts and less urbanized areas.12 Strictly recent immigrants in 2011 are those in the National Household Survey (NHS)who arrived since the last census in the summer of 2006.18of a population of approximately 5,080 persons (90 when including Taiwan). 13 Thedistribution is not uniform; 37% of tracts have no recent Chinese immigrants and innine tracts recent immigrants from China account for over 10% of the tract population.98% of tracts have at least one recent immigrant, with the mean number of 341, orapproximately 7% of tract residents.The distribution of immigrant clusters throughout the Vancouver CMA reveals someinteresting patterns. Figure 1 shows the distribution of the percentage recent Chineseimmigrants that make up of a census tract’s population. Though the highest percent-ages are in the cities of Vancouver and Richmond, there are nodes of concentrationthroughout the metro area. Figure 2 shows the same for all other immigrants. Heretoo non-Chinese recent immigrants are distributed throughout the CMA, though theyhave a particularly notable cluster in the suburb of Surrey, which is home to the CMA’slargest South Asian community. Figures 3 and 4 convert these percentages to percentilesin the distribution of immigrant percentage by census tract. Both those above the me-dian and the highest percentile tracts (> 80th percentile) are distributed throughoutthe CMA and not just clustered in a single area, though the largest clusters are incertain jurisdictions. For our empirical tests these distributions suggest that any resultswill not be a function of a particular neighbourhood, but will reflect broader geographicpatterns.Immigrants to Canada are admitted under a number of categories including refugee,family reunification, skilled worker, business, Canadian experience, live-in caregiver,and Provincial nominees. In 2010 approximately 281,000 immigrants were admitted toCanada. Of those, 4.8% were in the business category, which is overwhelmingly investorclass immigrants. 14 Table 2 shows the breakdown of immigrants in Canada and BritishColumbia by immigrant class. British Columbia, with a population share in 2011 of13.1% took in 15.7% of all immigrants, and for our purposes close to 50% of all investorclass immigrants. In this period nearly 92% of immigrants to British Columbia settledin the Vancouver CMA.13 The 2011 NHS survey estimates that in the Vancouver CMA, 40 percent of the meantract population is non-native born, and of the mean tract population of 5,080 persons.Over twenty percent of these, 595, are from Greater China. The count of persons forwhom the primary home language is a Chinese language is 560. The mean count ofrecent (last five years) immigrants is 340.14 The largest single class nationally is skilled worker, with a 42.5% share, family reuni-fication accounted for 21.5% and refugees for 8.8%.196 Empirical ResultsOur baseline specification follows the estimating equation shown in (2). The definitionof an investor immigrant tract is one with over the median percentage of recent Chineseimmigrants as described by (1). The identification of the investor program suspensioncomes from the relative difference in house prices before and after the suspension be-tween tracts with above the median number of recent Chinese immigrants as of 2011and those below. In Table 3 we present results for varying window lengths from three totwenty four months around the July 2012 suspension of the investor immigrant program.The regression includes juridstiction fixed effects .Relative to census tracts below the median number of recent Chinese immigrants, thosewith above the median concentration experienced price declines. The immediate post-announcement in column (1) for the three month windows shows a relative declineof 2.2%. This magnitude remains relatively unchanged up to the 12-month window,column (4), before becoming insignificant for the two-year window. These and all ofthe difference in differences regressions in the paper include standard hedonic controls,which with the exception of the number of bathrooms, all have the expected signs, andjurisdiction fixed effects. 15 16The three month price reaction seems too quick for it to have come from a declinein demand by arriving investor immigrants. We postulate that the results reflect theimmediate capitalization of the decline in future demand by local sellers and by devel-opers seeking to purchase older homes to teardown and renovate for wealthy immigrantsto purchase, in addition to a reduction in the inflow of investor immigrants from thesuspension.We further analyze the pre and post-event trends in Table 7 and the related discussionbelow. For the moment let us just mention that the effect disappears for the 24-mothwindow because the demand for destination neighbourhoods returns rather than a dis-persion of the negative demand shock to non-immigrant neighbourhoods.15 Hedonic controls are lot size and lot size squared, floor area and floor area squared,number of bedrooms, number of full and part bathrooms, unit aged and aged squared,and dummies for the presence of a pool, garage, and if the unit is fewer than ten yearsold.16 The number of recent immigrants from China is a positive co-variate with the numberof single family detached houses in a census tract that are redevelopments on the site ofan older teardown in regressions that also include tract population, median income, andthe total number of recent immigrants, where the estimated coefficient on the latter isnegative.20In Table 4, we run the same mean difference in difference regression that are shownin Table 3, but with different cut-offs defining what constitutes an investor immigranttract. For the six month window before and after July 2012 we raise the definitionof an immigrant investor tract from being those with above the median percentage ofrecent Chinese immigrants in the tract population, as used in Table 3, to as high as the80th percentile. In all the cases the comparison group is tracts with below the medianpercentage of recent Chinese immigrants as of 2011. Consequently, for regressions (2)through (4) of Table 4 we exclude transactions from tracts with above the medianpercentage of recent Chinese immigrants but below the cut-off used in the particularregression. With stricter definitions of investor immigrant destination tracts as beingthose with a higher percentage of recent Chinese immigrants the house price effects ofthe suspension are stronger, peaking at 2.6% lower prices after the suspension for thetracts at the 80th percentile or higher percentage of recent Chinese immigrants. Since thenumber of observations drops as we increase the concentration cut-off (the concentrationcut-off for non-immigrant tracts remains at 50th percentile), the significance level dropsslightly. But the coefficients themselves tend to increase, and remain strongly significant.Our interpretation is that as we impose a stricter definition of a likely investor immigrantneighbourhood, the price effects from the program suspension are stronger.Our designation of investor immigrant destination tracts as those with a higher than themedian percentage of recent Chinese immigrants is imprecise. All else equal, we wouldexpect investor immigrants to buy more expensive houses and choose more expensiveneighbourhoods from among those in which Chinese immigrants choose to settle. Totest for the higher house price effect, in Table 5 we estimate quantile regressions for fivedifferent percentile house values, instead of the mean regressions in Tables 3 and 4. Ingeneral, the negative effect of the suspension in the investor immigrant program is evenstronger when estimating the value of units higher in the price percentile distribution.Comparing the 25th and 7th percentiles, the absolute value of the coefficient estimatesfor all time periods are higher end when trying to fit the regression to the 75th percentile.This difference declines in half or more within two years. The difference in prices forthe lower two quantiles considered is smaller and generally not significant.Table 6 limits the analysis to tracts with the median property value in the upper half ofall tracts. The results are similar to the base specification, though the point estimatesare larger in absolute values than in the base regression. As in the previous regressions,the price decline diminishes by half with time. The largest effects are in the first threemonths. Though the differences between coefficient estimates for different time windowsare not statistically significant, the pattern of higher point estimates as we better targetcensus tracts and units more likely to be the choice of wealthy investor immigrantsis supportive of our conclusions that the price declines reflect market reaction to anexpected decline in future demand.Up to this point our specification just measures a mean difference in relative price levelsbetween houses in likely investor immigrant destination census tracts and those in theremaining tracts before and after the July 2012 investor immigrant program suspension.21As an alternative test we use the model as specified by Equation 3 to allow for trendeffects and test for differences in the different time paths of prices in the different tractsaround the program change. These results are presented in Table 7. Again we find aclear statistically different than zero fall in house prices in the tracts where investorimmigrants are likely to purchase homes. And again the effects dissipates over time.Though here in the case of the return calculation this happens within one year.The time pattern of the coefficients on post-July 12 and on the post-July 12 investorimmigrant tract reveal something of the pattern of the price effects. House prices inthe investor immigrant tracts fall those in the other tracts, but the recovery to the pre-July 2012 ratios does not occur because prices fall in response in the other areas, butby recovery in the investor tracts. Thus we do not see a ripple or transmission of priceshocks from one group of neighbourhoods to others. This is consistent with the argumentthat there is no native born flight from immigrant areas, otherwise prices in the otherareas would have fallen as demand for location by native-born home buyers shifted backto the investor immigrants areas after the program suspension. More likely, immigrant-rich neighbourhoods experience a return of high demand because both buyers and sellersrealized that the suspension of the program was a one-off event, rather than a first in asequence of immigration tightening measures. More importantly, potential immigrantsand their legal advisors in Canada discovered tjat there are other immigration channelsthat remained open.We preform a number of robustness tests on the data that serve the role of falsificationtests. The first two, in Table 8 and Table 9 report the estimation of Equation 2 exactlyas above except for the condominium sample. Table 8 replicates Table 3 just with con-dominium sales prices. We believe that investor immigrants have a stronger preferencefor more expensive and luxurious single-family houses. If true, then the condominiumsample offers a falsification test. All of the interaction coefficients reported in Table 8 areeither insignificant or positive. None of them are negative and significant. The secondfalsification test in Table 9 replicates the 90th percentile quantile regressions in Table5. As with Table 8, the results in Table 9 show no price declines even for higher pricedcondominium units. This suggests that it was specifically single family houses, and moreexpensive houses in particular, that were affected by the announcement, not the marketin general. This is what we would expect to see from a policy targeted towards wealthyimmigrants if indeed expectations of future demand were lowered by the suspension ofthe program.The second set of robustness tests use the percentage of non-Chinese recent immigrantsin place of the percentage of Chinese recent immigrants. The test is whether we arejust identifying a general effect of immigrant arrivals on local house prices or somethingunique to recent Chinese immigrants who are dramatically more likely to have beenadmitted to Canada under the investor class program. Tables 10 and 11 report theestimation of Equation 3 exactly as above except using non-Chinese immigrants. 17As noted above, immigrants from countries other than China and Taiwan represent17 China accounts for 23% of all immigrants coming to British Columbia. Other countries22less than 20% of the investor immigrants. Thus, non-Chinese immigrant concentrationoffers a way to separate the effect of immigration in general from immigration throughthe specific investor immigrant program that was discontinued. This is an interestingfalsification test because it verifies if some event about immigrants in general affectedthe real estate markets, rather than the suspension of the program itself.Houses in census tracts with higher percentages of recent non-Chinese immigrants trans-act for lower prices but are experiencing faster price appreciation than is case censustracts with below the median percentage of immigrants in general. These regressions,which include the same set of co-variates as above including jurisdiction fixed effects,reveal some interesting insights. Houses in census tracts with above the median per-centage of non-Chinese immigrants transact for 1.6 to 2.4% less than similar housesin the same jurisdiction but in tracts with below the median percentage of recent im-migrants. Over this period, immigrants accounted for nearly 80% of the metro area’spopulation growth. The tracts with more non-Chinese immigrants grew faster than didother tracts: the estimated coefficient on the interaction between post July 2012 andabove the median percentage of non-Chinese immigrant in Table 10 ranges from 1.7%to 2.0%. While there may be a number of reasons for this positive relationship, theimportant point related to our work is that the interaction coefficient is not negative. Inother words, it was specifically markets favored by investor immigrants that were nega-tively affected. None of the other markets we consider experienced a negative impact. Itdoes also suggest a broader positive effect of immigration on house price appreciation.However, we lack an exogenous shock to effectively test this more general implication.In Table 11, there is generally no relationship between non-Chinese immigrants andprices at the 90th percentile quantile, so whatever the effect of immigration it is onlower values homes.We have further performed numerous additional robustness tests, not reported in thepaper. Our results are robust to moving the event date forward by one month to accountfor potential delay in transactions. Our results are also robust to various additional fil-tering of the data to exclude outliers and to windsorising the data at 1% level. Wealready employ t-statistics and confidence intervals robust to serial correlation and het-eroscedasticity. We also do a panel difference in differences test on overall house prices inAustralian cities, using Chinese immigrant destination cities Melbourne and Sydney asthe treatment group. Australia received a similar number of Chinese immigrants as didCanada, between 2006 and 2011 146,000 for Canada and 135,000 Chinese immigrantsfor Australia. If the effect we observe is because of an internal China cause, then wewould expect to see reduced housing demand from a drop in immigrants in those Aus-tralian cities favored by Chinese immigrants. 18 Following July 2012, the difference inwith large immigration inflow into BC are the Philippines (17.3%) and India (14%). Theremaining countries include Korea, USA, England, Iran, Taiwan, Japan, among others,all with a six percent or less share of total immigration.18 Australian immigration data is by state, not metropolitan area, but each state’s cap-23house price appreciation between these two cities and other Australian cities was largerthan it had been prior to July 2012. This suggests that what we observe in our data ismore likely to be from a Canada effect than a change in the outflow from China.7 ConclusionWe exploit a sudden and unexpected suspension of a popular investor immigrant pro-gram in Canada to study the effect of immigration on real estate prices. We find strongevidence that market segments favored by investor immigrants underperformed the restof the market following the suspension announcement. This finding is highly robust tomodel specification and sample selection.These results contribute to the discussion of the effects of both immigration and capitalinflows on house prices because the group we study, investor immigrants, representsboth. Unlike Saiz and Wachter (2011), our findings show that immigration can resultin higher local house prices as demand from immigrants, at least wealthy immigrants,dominates any flight by native born. This is consistent with Ibraimovic and Masiero’s(2014) work on immigration in Switzerland, that while locals prefer to locate away fromimmigrants, this effect attenuates with education level, which we take to be positivelycorrelated with wealth. Therefore, our findings are possibly not generalizable to allimmigrant groups, but apply to wealthy immigrants. We cannot determine if this ispurely a wealth effect from capital immigrants bring or social-cultural effects as wecannot identify immigrants by country or by more refined household characteristics atthe tract level.Our results are unlikely to be entirely because of the declines in the number of arriv-ing immigrants. The major share of the maximum price effect (73% in the base case)occurs within the first three months, well below the time period by which those whoreceived their visa are required to enter Canada. We believe this reflects a change in theexpectation of local sellers and developers who perceived the suspension of the investorimmigrant program to be a negative shock to future demand, which became capitalizedin lower relative prices immediately.Beyond the immediate implications related to immigration, our work offers a measure ofownership demand elasticity. Our findings suggest that real estate prices are at least inpart driven by total demand for ownership, rather than by asset pricing fundamentals.As we discussed above, the investor immigrant program is small relative to the size ofthe overall market and is therefore unlikely to change the economic realities of the areaital city metropolitan area has a dominant share of state population. Victoria and NewSouth Wales have a 70% share of Chinese immigrants to Australia compared with a49% share of non-Chinese immigrants.24and impact rents or discount rates. 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Housing Markets and Migration: Evidence fromNew Zealand. New Zealand Department of Labour Economic Impacts of ImmigrationWorking Paper SeriesSuher, Ml. (2016). Is Anybody Home? The Impact and Taxation of Non-Resident Buy-ers. Furman Center for Real Estate and Urban Policy, NYU Working Paper.289 Figures and Tables29Fig. 1. The figure shows the concentration of recent Chinese immigrants as a prortion of total population bycensus tract in the Vancouver CMA.30Fig. 2. The figure shows the concentration of recent immigrants other than Chinese as a prortion of totalpopulation by census tract in the Vancouver CMA.31Fig. 3. The figure shows the percentile of recent Chinese immigrants as a prortion of total population by censustract in the Vancouver CMA.32Fig. 4. The figure shows the percentile of recent non-Chinese immigrants as a prortion of total population bycensus tract in the Vancouver CMA.33(1) (2) (3) (4) (5)Single Family N mean sd min maxLot size 000sf 722,582.000 8.020 6.781 0.533 87.120Finished area 000sf 722,987.000 2.424 0.954 0.264 9.994Number of bedrooms 722,969.000 3.911 1.198 0.000 14.000Pool 722,987.000 0.035 0.183 0.000 1.000lnP 722,987.000 12.346 0.895 9.210 18.664Number of bathrooms (full+half) 722,987.000 2.760 1.229 0.000 11.000Garage (one or two stalls) 722,987.000 0.782 0.480 0.000 5.000Age 662,936.000 14.961 14.062 0.000 106.000Proportion Recent Chinese Immigrants 719,536.000 0.013 0.020 0.000 0.137propRecentOther 719,536.000 0.042 0.030 0.000 0.221(1) (2) (3) (4) (5)Multi-family N mean sd min maxFinished area 000sf 428,107.000 0.910 0.293 0.251 8.750Number of bedrooms 410,874.000 1.675 0.603 0.000 7.000Pool 428,107.000 0.000 0.000 0.000 0.000lnP 428,107.000 12.157 0.691 9.210 19.902Number of bathrooms (full+half) 428,107.000 1.516 0.563 0.000 10.000Garage (one or two stalls) 428,107.000 0.001 0.023 0.000 1.000Age 427,443.000 9.147 9.612 0.000 87.000Proportion Recent Chinese Immigrants 428,002.000 0.020 0.027 0.000 0.131propRecentOther 428,002.000 0.064 0.031 0.000 0.214Table 1The table shows the summary statistics for the data by single family and multi-family properties. The proportionof recent Chinese immigrants and recent investor immigrants from all countries is computed as a ratio to totalpopulation in a census tract. Each real estate transaction is assigned this ratio based on its location.34Immigration Class Canada BC BC Share (%)Family 60,223 10,867 18Refugee 24,697 1,667 6.7Skilled Worker 119,357 16,661 14.0Canadian Experience 3,917 572 14.6Prov/Terr Nominee 36,430 4,900 13.5Live-In Care Giver 13,911 2,884 20.7Entrepreneur 1,087 234 21.5Investor 11,715 5,510 47.0Self-Employed 500 116 23.2Other 8,853 777 8.8Total 280,690 44,188 15.72011 Population (000) 33,477 4,400 13.1Table 2The table shows the breakdown of Canadian and British Columbia immigrants as of 2011.Sources: Statistics Canada, BC Statistics, Citizenship and Immigration Canada35(1) (2) (3) (4) (5)VARIABLES +/- 3 months +/- 6 months +/- 9 months +/- 12 months +/- 24 monthsLot size 000sf 0.093*** 0.087*** 0.088*** 0.096*** 0.096***(12.16) (13.51) (17.03) (22.53) (31.03)Lot size squared -0.005*** -0.004*** -0.004*** -0.005*** -0.004***(-8.30) (-9.09) (-11.08) (-15.05) (-20.05)Pool 0.050** 0.048*** 0.057*** 0.058*** 0.048***(2.52) (3.15) (5.09) (7.01) (8.54)Finished area 000sf 0.205*** 0.203*** 0.187*** 0.171*** 0.173***(9.41) (11.08) (12.80) (14.61) (20.92)Finished area squared -0.014*** -0.013*** -0.010*** -0.008*** -0.008***(-3.53) (-3.77) (-3.73) (-3.70) (-5.26)Number of bedrooms -0.012*** -0.011*** -0.011*** -0.012*** -0.015***(-5.05) (-5.28) (-6.69) (-9.19) (-15.19)Number of bathrooms (full+half) -0.007** -0.008*** -0.005** 0.001 0.003**(-2.16) (-2.96) (-2.34) (0.56) (1.97)Garage (one or two stalls) 0.037*** 0.040*** 0.047*** 0.045*** 0.039***(7.48) (9.83) (14.57) (17.72) (21.48)Age -0.006*** -0.005*** -0.006*** -0.007*** -0.007***(-7.25) (-7.80) (-12.10) (-17.47) (-24.09)Age Squared 0.000*** 0.000** 0.000*** 0.000*** 0.000***(2.66) (2.29) (5.18) (8.86) (11.55)Less than 10 years old 0.014 0.016** 0.011* 0.010** 0.018***(1.40) (1.98) (1.77) (2.06) (4.90)postJuly2012 0.010** 0.006 0.006* 0.014*** 0.064***(2.00) (1.47) (1.72) (5.22) (33.49)Chinese Tract 0.026** 0.018** 0.022*** 0.021*** 0.013***(2.42) (2.04) (3.16) (3.75) (3.19)postJuly2012 * Chinese Tract -0.022** -0.017** -0.023*** -0.020*** 0.003(-2.39) (-2.27) (-3.85) (-4.32) (1.00)Constant 13.902*** 13.928*** 13.950*** 13.944*** 13.902***(258.38) (326.56) (418.89) (523.74) (724.22)Observations 6,328 9,302 14,860 22,173 46,291R-squared 0.865 0.868 0.866 0.868 0.852Jurisdiction effects Yes Yes Yes Yes YesRobust t-statistics in parentheses*** p<0.01, ** p<0.05, * p<0.1Table 3The table reports the results of a basic difference-in-difference model of log-transaction prices using only Chineserecent immigrant data. The coefficient estimate on variable ”post-July, 2012” captures the change in overall pricesfollowing the suspension of the investor immigrant program. The coefficient estimate on the interaction variable”post-July, 2012 * Chinese neighbourhood” captures the marginal change in prices in Chinese neighbourhoodson top of the overall change. The table reports estimates for five different event windows: plus/minus 3, 6, 9, 12,and 24 months. The change in overall prices around the announcement is generally not significant. However, themarginal change in price for properties located in Chinese neighbourhoods, as captured by the interaction term,is strongly significant within 12 months of the annoucement. The effect dissipates for longer time frames.36(1) (2) (3) (4)VARIABLES 50th percentile 60th percentile 70th percentile 80th percentilepostJuly2012 0.006 0.007* 0.007* 0.007*(1.47) (1.69) (1.74) (1.72)Chinese Tract 0.018** 0.026** 0.044*** 0.069***(2.04) (2.36) (2.75) (3.82)postJuly2012 * Chinese Tract -0.017** -0.019** -0.020** -0.026**(-2.27) (-2.45) (-2.01) (-2.08)Observations 9,302 8,553 7,559 6,931R-squared 0.868 0.873 0.881 0.880Jurisdiction and Hedonic effects Yes Yes Yes YesRobust t-statistics in parentheses*** p<0.01, ** p<0.05, * p<0.1Table 4The table reports the results of the same difference-in-difference model of log-transaction prices as reportedin Table 3 for four definitions of a Chinese neighbourhood using the 50th, 60th, 70th, and 80th concentrationpercentiles. The cut-off for non-Chinese neighbourhood is held at the 50th percentile. The coefficient estimate onvariable ”post-July, 2012” captures the change in overall prices following the suspension of the investor immigrantprogram. The coefficient estimate on the interaction variable ”post-July, 2012 * Chinese neighbourhood” capturethe marginal change in prices in Chinese neighbourhoods on top of the overall change. Thus, observations betweenthe two percentile cut-offs are excluded from the second, third, and forth models. The marginal change oftransaction price for properties located in Chinese neighbourhoods, as captured by the interaction term, isstrongly significant regardless of the specific cut-off level used to split the sample.37(1) (2) (3) (4) (5)VARIABLES +/- 3 months +/- 6 months +/- 9 months +/- 12 months +/- 24 months10th perentile -0.036** -0.027 -0.022 -0.023** 0.014(-1.99) (-1.55) (-1.62) (-2.18) (1.52)(1) (2) (3) (4) (5)VARIABLES +/- 3 months +/- 6 months +/- 9 months +/- 12 months +/- 24 months25th perentile -0.015 -0.003 -0.011 -0.015** 0.007(-1.00) (-0.26) (-1.21) (-2.53) (1.32)(1) (2) (3) (4) (5)VARIABLES +/- 3 months +/- 6 months +/- 9 months +/- 12 months +/- 24 months50th perentile -0.021*** -0.018*** -0.016*** -0.017*** 0.000(-2.81) (-2.98) (-3.45) (-4.33) (0.06)(1) (2) (3) (4) (5)VARIABLES +/- 3 months +/- 6 months +/- 9 months +/- 12 months +/- 24 months75th perentile -0.030*** -0.021*** -0.021*** -0.020*** -0.008***(-3.78) (-3.91) (-4.54) (-5.19) (-2.90)(1) (2) (3) (4) (5)VARIABLES +/- 3 months +/- 6 months +/- 9 months +/- 12 months +/- 24 months90th perentile -0.028** -0.026*** -0.016** -0.018*** -0.013***(-2.44) (-3.02) (-2.20) (-3.23) (-3.41)t-statistics in parentheses*** p<0.01, ** p<0.05, * p<0.1Table 5The table reports the results of the same difference-in-difference model of log-transaction prices as reported inTable 3 except using quantile regression for five separate quantiles and five time windows. The table reports theinteraction term between Chinese neighbourhoods and post-July, 2012, the remaining coefficients are availableupon request. The interaction between post-July and Chinese neighbourhood variables is negative and stronglysignificant for the 50th or higher percentiles. The interaction term is generally not significant for the 10th and25th quantile. The effect dissipates for longer time frames.38(1) (2) (3) (4) (5)VARIABLES +/- 3 months +/- 6 months +/- 9 months +/- 12 months +/- 24 monthspostJuly2012 0.021** 0.010 0.002 0.013** 0.080***(2.08) (1.24) (0.34) (2.32) (20.79)Chinese Tract -0.016 -0.015 -0.001 0.004 0.003(-0.95) (-1.13) (-0.06) (0.46) (0.38)postJuly2012 * Chinese Tract -0.034** -0.024** -0.030*** -0.025*** -0.017***(-2.32) (-2.09) (-3.19) (-3.48) (-3.27)Observations 2,928 4,304 6,904 10,592 22,255R-squared 0.836 0.842 0.830 0.833 0.813Jurisdiction and Hedonic effects Yes Yes Yes Yes YesRobust t-statistics in parentheses*** p<0.01, ** p<0.05, * p<0.1Table 6High Value Tracts (pct50s05 >= 50) The table reports the results for the same difference-in-difference modelof log-transaction prices as reported in Table 3 except using only transactions with above-average value. As inthe case of Table 3 , the interaction between post-July and Chinese neighbourhood variables is negative andstrongly significant for time windows up to +/- 24 months. The effect is smaller for the longer time windows.39(1) (2) (3) (4)VARIABLES +/- 3 months +/- 6 months +/- 9 months +/- 12 monthst 0.005*** 0.005*** 0.002*** 0.001***(3.22) (5.03) (4.69) (3.68)t * postJuly2012 -0.011** -0.011*** -0.004*** -0.001(-1.98) (-4.77) (-4.09) (-1.30)t * Chinese Tract 0.001* 0.001* 0.001* 0.000(1.95) (1.84) (1.96) (0.62)t * postJuly2012 * Chinese Tract -0.016** -0.008*** -0.005*** -0.001*(-2.25) (-2.74) (-3.30) (-1.65)Observations 6,328 9,302 14,860 22,173R-squared 0.865 0.869 0.866 0.868Jurisdiction and Hedonic effects Yes Yes Yes YesRobust t-statistics in parentheses*** p<0.01, ** p<0.05, * p<0.1Table 7The table reports the estimates from a piece-wise linear model with a break on July, 2012 using Chinese immigrantdata. The coefficient estimates for time capture the baseline trend in prices before the announcement event.The coefficient estimate for ”time * postJuly2012” captures the marginal change in baseline trend after theannouncement event. The coefficient estimate for variable ”time * Chinese” captures the marginal trend, inaddition to the base trend, for Chinese neighbourhoods before the announcement. Finally, the coefficient estimatefor the interaction term ”t * postJuly2012 * Chinese” captures the marginal post-announcement trend for Chineseneighbourhoods. All estimates are reported for four separate time windows: plus/minus 3, 6, 9, and 12 months.The marginal trend for Chinese neighbourhoods post announcement is negative and significant for all eventwindows considered.40(1) (2) (3) (4) (5)VARIABLES +/- 3 months +/- 6 months +/- 9 months +/- 12 months +/- 24 monthsFinished area 000sf 1.388*** 1.448*** 1.398*** 1.404*** 1.365***(23.76) (23.50) (27.62) (32.43) (41.70)Finished area squared -0.174*** -0.194*** -0.184*** -0.182*** -0.162***(-8.98) (-9.06) (-10.21) (-11.57) (-13.47)Number of bedrooms -0.003 -0.005 0.002 -0.002 -0.007**(-0.34) (-0.69) (0.30) (-0.53) (-2.15)Number of bathrooms (full+half) 0.025*** 0.019*** 0.018*** 0.013*** 0.004(3.16) (2.82) (3.60) (3.19) (1.45)Age -0.030*** -0.029*** -0.028*** -0.029*** -0.028***(-17.41) (-21.85) (-29.65) (-34.49) (-52.75)Age Squared 0.000*** 0.000*** 0.000*** 0.000*** 0.000***(9.15) (11.53) (15.23) (17.83) (27.06)Less than 10 years old -0.055*** -0.041*** -0.035*** -0.034*** -0.028***(-3.32) (-3.11) (-3.54) (-4.16) (-5.07)postJuly2012 -0.022*** -0.029*** -0.010* -0.012*** 0.004(-2.66) (-4.24) (-1.86) (-2.69) (1.38)Chinese 0.003 0.012 0.013** 0.011** 0.008**(0.31) (1.48) (2.09) (1.99) (2.06)postJuly2012 * Chinese 0.010 0.005 -0.006 0.007 0.023***(0.85) (0.57) (-0.87) (1.24) (5.78)Constant 12.557*** 12.519*** 12.465*** 12.460*** 12.481***(213.39) (221.52) (260.77) (306.39) (444.17)Observations 3,506 5,307 8,903 12,678 26,386R-squared 0.930 0.926 0.922 0.919 0.914Jurisdiction effects Yes Yes Yes Yes YesRobust t-statistics in parentheses*** p<0.01, ** p<0.05, * p<0.1Table 8The table reports the same estimation as the one reported in Table 3, except for condominium units. Condo-minium units are typically less desirable for Chinese immigrants, especially the ones with sufficient wealth toqualify for the investment immigrant program. As such, the condominium sample serves as a falsification test.As expected, the marginal change in post-July, 2012 prices in Chinese neighbourhoods is indistinguishable fromzero or positive.41(1) (2) (3) (4) (5)VARIABLES +/- 3 months +/- 6 months +/- 9 months +/- 12 months +/- 24 monthspostJuly2012 -0.034** -0.040*** -0.003 -0.013 0.006(-1.98) (-2.97) (-0.25) (-1.58) (1.06)Chinese Tract 0.000 0.012 0.010 0.004 0.006(0.01) (0.83) (0.78) (0.37) (0.90)postJuly2012 * Chinese 0.022 0.025 -0.008 0.018* 0.032***(1.02) (1.48) (-0.59) (1.70) (4.28)Observations 3,506 5,387 8,903 12,678 26,386Jurisdiction and Hedonic effects Yes Yes Yes Yes Yest-statistics in parentheses*** p<0.01, ** p<0.05, * p<0.1Table 9The table reports the results of the same difference-in-difference model of log-transaction prices for condominiumunits as reported in Table 8 except using quantile regression at the 90th percentile of property values. As inthe case of Table 8, the interaction between post-July and Chinese neighbourhood variables is not significant orpositive for all event windows considered.42(1) (2) (3) (4) (5)VARIABLES +/- 3 months +/- 6 months +/- 9 months +/- 12 months +/- 24 monthspostJuly2012 -0.006 -0.007 -0.010*** -0.001 0.057***(-0.98) (-1.51) (-2.70) (-0.41) (27.35)Other Immigrant Tract -0.024*** -0.020*** -0.016*** -0.017*** -0.021***(-2.98) (-2.98) (-3.14) (-3.78) (-6.53)postJuly2012 * Other Immigrant Tract 0.019** 0.017** 0.017*** 0.018*** 0.020***(2.20) (2.42) (3.01) (3.97) (6.16)Observations 6,328 9,302 14,860 22,173 46,291R-squared 0.865 0.868 0.866 0.868 0.852Jurisdiction and Hedonic effects Yes Yes Yes Yes YesRobust t-statistics in parentheses*** p<0.01, ** p<0.05, * p<0.1Table 10The table reports the same estimation results as Table 3, except for all non-Chinese immigrants. Non-Chineseimmigrants are less likely to be impacted by the suspension of the immigrant program, and/or are less likely tohave an impact on the real estate markets. The coefficient estimate on variable ”post-July, 2012” captures thechange in overall prices following the suspension of the investor immigrant program. The coefficient estimateon the interaction variable ”post-July, 2012 * Other neighbourhood” captures the marginal change in pricesin non-Chinese immigrant neighbourhoods on top of the overall change. The table reports estimates for fivedifferent event windows: plus/minus 3, 6, 9, 12, and 24 months. The change in overall prices around theannouncement is generally not significant. However, the marginal change in price for properties located innon-Chinese immigrant neighbourhoods, as captured by the interaction term, is actually positive regardless ofthe specific event window. In other words, high non-Chinese immigrant concentration neighbourhoods did notexperience a price decline around the time of the investor program suspension.43(1) (2) (3) (4) (5)VARIABLES +/- 3 months +/- 6 months +/- 9 months +/- 12 months +/- 24 monthspostJuly2012 -0.005 -0.012** -0.006 0.000 0.038***(-0.72) (-2.05) (-1.38) (0.13) (16.01)Other Immigrant Tract -0.022** -0.025*** -0.024*** -0.023*** -0.022***(-2.32) (-3.19) (-3.85) (-4.14) (-6.05)postJuly2012 * Other Immigrant Tract -0.012 -0.006 0.004 0.010* 0.010***(-1.10) (-0.70) (0.52) (1.80) (2.69)Observations 6,328 9,302 14,860 22,173 46,291Jurisdiction and Neighborhood effects Yes Yes Yes Yes Yest-statistics in parentheses*** p<0.01, ** p<0.05, * p<0.1Table 11The table reports the results of the same difference-in-difference model of log-transaction prices for other immi-grants as reported in Table 10 except using quantile regression at the 90th percentile of property values. As inthe case of Table 10, the interaction between post-July and Chinese neighbourhood variables is not significantor is positive for all event windows considered.44


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