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Emerging Housing Markets in Moldova
Journal of Housing Economics 10, 419–428 (2001) doi:10.1006/jhec.2001.0302, available online at http://www.idealibrary.com on
Emerging Housing Markets in Moldova John E. Anderson1 Department of Economics, University of Nebraska, Lincoln, Nebraska 68588 E-mail: [email protected] Received December 12, 2000 This paper provides tentative evidence on the extent to which market forces are now responsible of the determination of housing prices in the two principle cities of Moldova, a former Soviet republic. Microlevel data for flats in the two principal cities of Chisinau and Tiraspol are used to estimate hedonic price equations in an attempt to discern the extent to which market forces are now determining prices. Despite the fact that Moldova is taking a rather slow approach to economic transition in general, with the economy in a continued decline with GDP per capita falling, these data reveal a substantial degree of housing market rationality based on market forces. 䉷 2001 Elsevier Science Key Words: housing markets; economic transition; hedonic prices. Journal of Economic Literature Classification Numbers: R1, R5, H7.
1. INTRODUCTION The extensive housing stock in countries of the former Soviet Union (FSU) has undergone and continues to undergo privatization, with the extent varying substantially from country to country. Allocation mechanisms used for housing bore no resemblance to market forces in the past, with central planning ignoring the information that would be contained in prices. With independence, however, most countries of the FSU have privatized at least some housing and now rely on market forces, at least partially, to allocate resources in the housing sector. This paper examines the extent to which market forces are now responsible for the determination of housing prices and explains what implications follow from the reliance on market forces. Analysis of data drawn from the emerging housing market in Moldova over the period 1998–1999 is presented in the paper. Moldova has made good progress in privatizing the Soviet housing stock and most families now own their own flats. Microlevel data for flats in the capital city, Chisinau, with a population of nearly one million, and Tiraspol, a major industrial city in the break-away region 1
The author served as tax policy advisor on the USAID Fiscal Reform Project and the Local Government Reform Project in Moldova since 1998. The opinions expressed in this paper are those of the author alone, however, and should not be construed as those of USAID, KPMG Barents Group, the government of Moldova, or any of its agencies. 419 1051-1377/01 $35.00 䉷 2001 Elsevier Science All rights reserved.
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of Trans-Dneister, have been used to estimate hedonic price equations in an attempt to discern the extent to which market forces are now determining prices. Despite the fact that Moldova is taking a rather slow approach to economic transition in general, with the economy in a continued decline with GDP per capita falling, these data reveal a high degree of housing market rationality based on market forces. In fact, regression models based on physical characteristics and location information explain a high percentage of the variation in housing prices, revealing that forces are at work despite a good deal of noise in the system due to currency depreciation, exogenous shocks due to Russian economic events, and other factors. While the results reported in this paper must be considered tentative, given the small data sets and obvious data limitations, there is an encouraging degree of clear market rationality revealed in the hedonic equations. Market forces are beginning to work despite numerous institutional limitations.
2. PRIVATIZATION AND THE DEVELOPMENT OF HOUSING MARKETS Privatization of Housing in Transition Economies The situation prereform has been described by Svejnar (1991, p. 126) as follows: While most socialist countries permitted limited leasing and de facto ownership of land, a market for land was basically nonexistent. A real estate market has emerged in recent years, although most housing is still rented at controlled prices that are significantly below market equilibrium. Housing costs have constituted a relatively small fraction of consumer expenditures for most households, although a significant group of urban residents pay substantial rents for deregulated housing, in some countries through a black market. The maintenance of houses was generally poor, and considerable excess demand for housing existed at the subsidized rental prices. On the other hand, the system succeeded in avoiding blatant urban poverty.2
Alexeev (1988a, 1988b) provides evidence that in the later part of the Soviet era market forces were already beginning to replace administrative rationing in allocating scarce housing resources in Russia.3 Since independence there have been varying degrees of privatization among the FSU republics. While privatization has proceeded at different paces in each of the FSU republics, most observers would agree that the process is essentially completed in many republics, but is just over half finished in Russia, according to Guzanova (1997, p. 8). Once the housing stock is privatized, however, we must be concerned with 2 Another economic impact related to housing is the effect of crowding on labor productivity, as discussed in Hacker (1999). 3 See Buckley and Gurenko (1998) for a critique arguing that Russian households were not able to beat the system and that Alexeev’s income elasticity estimates are biased upward.
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the establishment of a secondary market for homes. In particular, we are interested in knowing to what extent market mechanisms begin to work in the allocation of housing units. To what extent do the forces of supply and demand begin to manifest themselves among the noise observed in house prices? Since the process of transition involves very substantial changes in relative prices between private and public goods, there are important distributional implications to consider, as well.4 Transition may bring a growing share of expenditures on housing, for example, as noted by Lanjour et al. (1998). Guzanova (1997) found that in the Russian experience, privatization of housing has resulted in disparate effects on various population groups. Those most likely to have their flats privatized include pensioners and relatively well-off families. The pensioners are by far the larger group and are generally reluctant to sell their homes once they have been privatized. They are immobile and not likely to participate in housing transactions. The second and smaller group is composed of relatively well-off families, who can be expected to become active participants in the housing market. Her research also reveals that high-quality flats in city centers are much more likely to be privatized than other homes. Specifically, she finds that quality of construction and location are important determinants of the likelihood of privatization. Other factors that have a bearing on the decision to privatize include the demographic characteristics of the household, the value orientations and level of education of the household, and the income level of the household. Daniell and Struyk (1997) also provide early evidence on the development of housing markets in Russia. Their work emphasizes early policy reforms, including fundamental legal reforms, and assesses whether those reforms were effective in developing a market orientation in the housing sector. Using longitudinal data they track private ownership, residential mobility, housing conditions, and housing affordability. They demonstrate that progress was clearly made in moving to functioning housing markets during the early years of independence. Privatization of Housing in Moldova Moldova is a small country and former Soviet republic west of Ukraine and east of Romania that has some 4.5 million residents. Independence from the USSR came in 1991, but bitter rivalries between ethnic Romanians and ethnic Russians complicated by the presence of the Soviet 14th army in the eastern part of the country resulted in a civil war during 1992–1993. The small breakaway region east of the Nistru River, called Transdneister, declared independence itself, but has not been recognized as a sovereign state by any other state. An uneasy ceasefire has been maintained, but a political resolution to this problem has not yet been accomplished. 4 For estimates of the distribution of income in Eastern Europe, and impacts of economic transition, see Atkinson and Micklewright (1992).
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Privatization of the housing stock is nearly complete in Moldova, as the government moved quickly after independence to privatize housing units, both flats and detached houses. There was a substantial share of the rural village housing stock that was privately owned in the Soviet era in Moldova, due to the nature of communes and villages (often consisting of several communes). In villages and communes, families had for the most part built their own homes on state-owned land. The government recognized those homes as privately owned. After independence, homeowners were permitted to keep their homes and an extensive program of land privatization has been quite successful. The former collective farms, both kolkhozes and sovkhozes, have been or are currently in the process of being privatized. Each of the n workers on the collective farm is given title to 1/n of the crop land, orchard land, and vineyard land. A secondary market is just beginning to develop for land parcels that have been privatized. Data on market values of these properties are insufficient to permit modeling of prices. Early indications, however, reveal that market prices are below the old Soviet-era normative prices based on intricate fertility indices. Urban residents typically lived in Soviet-style high-rise apartment buildings. Distinct vintages of homes are discernable, ranging from Stalin houses to Khrushchev houses to more modern houses: After independence, families were given the opportunity to purchase the flat in which they lived at very low cost, practically giving the flats to families. As an aside, it is interesting to note the animosity of village dwellers toward city dwellers when the issue of property taxation is raised. Village dwellers think it is quite unfair that they should be asked to pay a property tax on their homes, since they built their homes themselves. They claim that city dwellers were given their homes and should therefore be asked to pay a property tax. The obvious fact that the city dwellers received housing as a form of implicit wage paid by the state enterprise for which they worked is lost in this view. It was common in the Soviet system for railroad workers, for example, to live in a high-rise complex built for them by the state. In some cases, state enterprise workers actually built high-rise apartment buildings themselves, which they then occupied. In the minds of Moldovan village people, however, there are fundamental differences in the manner in which housing was obtained that have a bearing on public policy. In Chisinau, the price per square meter for the median home was $363.64 in 1998–99, while in Tiraspol the median price was $220.34. These figures can be compared to the Moscow average price of $610 (fourth quarter of 1996) reported in Guzanova (1997, p.19).5 Lower prices in Moldova are to be expected, since these Moldova cities are smaller than Moscow and the income level of the population is lower. Within Moldova, the higher price per square meter in Chisinau is also consistent with expectations, since Chisinau is the largest city in the country and is responsible for producing a large share of the country’s GDP. 5
For a detailed view of the experience of Russian cities in transition, see de Melo and Ofer (1999).
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Chisinau Housing Market Chisinau is the capital city of Moldova, home to some 800,000 residents. It is also home to most of the country’s business activity, generating a large share of Moldova’s GDP. The city is organized into eight districts, spread over the geographic area settled. The housing stock of Chisinau consists primarily of soviet-era high-rise homes, or apartment buildings. In addition, there is a substantial core of detached single family homes as well, primarily located in the Center and Tele Center districts, and in the historic district of Posta Vecha. With nearly all housing units privatized since independence, an active real estate market has emerged in Chisinau. Flats and detached homes are bought and sold, with and without the assistance of real estate brokers. A number of brokerage services have sprung up, with intense competition among them for listings. In fact, the sense of competition is so intense that there is no cooperation among brokers. Listings are treated as proprietary and there is no multiple listing service. Tiraspol Housing Market Tiraspol is a major industrial city in the Transdneister region of Moldova, east of the Nistru River. It is the home of the nation’s major industrial enterprises and electrical generation facilities, as well as of former Soviet military installations. This region is ideologically tied more closely to Soviet-era central planning methods of allocation rather than to market forces. Hence, one might expect that markets would not be used or permitted to allocate resources to such a great extent in this region. At a practical level, however, this region functions as one large free trade zone, with alleged traffic in all kinds of commodities, including weapons, drugs, and humans. From this point of view, it may well be the case that market forces are even freer to operate in this region than elsewhere in the country. 3. MODELS OF HOUSE PRICES Simple hedonic models are estimated for Chisinau and Tiraspol, with both physical characteristics and location characteristics used as explanatory variables. Similar models are estimated for both cities in order to illustrate the economic forces at work determining house prices and also to facilitate comparison of the results. Both samples are small and the results reported can only be considered preliminary, pending further research with more elaborate models and more comprehensive data. Chisinau Model The Chisinau sample includes observations on homes sold in 1999, ranging in price from $2,850 to $15,500. The average sale price was $9,845. Home size
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JOHN E. ANDERSON TABLE I Descriptive Statistics Chisinau Sample (n ⫽ 52)
Tiraspol Sample (n ⫽ 80)
Variable
Mean
Standard error
Variable
Mean
Standard error
Price ($) Log of price Total area Total area squared Rooms Relative floor Top floor Botanica Bubuieci Buicani Durlesti Posta Vecha Riscani Tele Center
9,845 9.1459 44.0577 2,008.635 1.7115 0.5873 0.1346 0.3654 0.0192 0.2500 0.0192 0.0577 0.0962 0.0577
2,854 0.3359 8.2993 689.1732 0.5475 0.2894 0.3446 0.4862 0.1387 0.4372 0.1387 0.2354 0.2977 0.2354
Asking price ($) Log of asking price Total area Total area squared Rooms Relative floor Top floor Balca Borodinca Kirov Krkazar
7,053 8.7756 53.1550 3,042.175 2.2250 0.5984 0.2250 0.3375 0.2125 0.0500 0.1250
2,749 0.4400 14.8143 1,563.535 0.7287 0.3029 0.4202 0.4758 0.4117 0.2193 0.3328
was 44 square meters of living space, on average, including 1.7 rooms. Table I provides descriptive. The data set consists of both sales prices and appraisals by professional real estate agents.6 Coefficient estimates for a simple hedonic model are presented in Table II. The dependent variable is the natural logarithm of the house price. Explanatory variables include measures of the size of the housing unit, its position within the building, and location within the city (by district). This model explains 69.52% of the variation in the log of price, indicating that a few objective variables can account for a large percentage of the observed variation in price. Despite all the limitations on housing market development, such as the lack of a mortgage market, there is a strong degree of rationality in prices. Total area and its square are both significant explanatory variables in this model. The positive sign on the total area variable and the negative sign on its square indicate that price rises with area at a declining rate. The number of rooms is only weakly significant, indicating that once area and its square are taken into account, the number of rooms in the home does not affect price very much. While flats in Moldova are always referred to by the number of rooms, for example a one-room or two-room flat, this designation apparently signals the overall size of the flat, not primarily the number of rooms into which it is divided. Two variables are included in the model to pick up effects of location within 6 Statistical tests indicate that the appraisal data do not differ significantly from the sales data in the reported hedonic equations.
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HOUSING MARKETS IN MOLDOVA TABLE II House Price Models Chisinau Model Variable Constant Total area Total area squared Rooms Relative floor Top floor Botanica Bubuieci Buicani Durlesti Posta Vecha Riscani Tele Center N R2 F Log likelihood
Tiraspol Model
Coefficient Standard error a
6.4079 0.1034a ⫺0.0010a 0.1155e 0.2884b ⫺0.1132 ⫺0.0863 ⫺1.1794a ⫺0.1130 ⫺0.4172a ⫺0.3533a 0.0050 ⫺0.1979c 52 0.6952 10.6924 21.3159
0.6359 0.0320 0.0004 0.0932 0.1205 0.1076 0.0970 0.1325 0.0876 0.1294 0.1004 0.1042 0.1072
Variable Constant Total area Total area squared Rooms Relative floor Top floor Balca Borodinca Kirov Krkazar
n R2 F Log likelihood
Coefficient Standard error 6.6589a 0.0619a ⫺0.0004a 0.0267 0.0504 ⫺0.1712a ⫺0.1561a ⫺0.1355a ⫺0.4653a ⫺0.1474a
0.3266 0.0131 0.0001 0.0614 0.0747 0.0639 0.0467 0.0543 0.0999 0.0516
80 0.8818 66.4732 42.9144
Note. Cells list coefficients, with standard errors in parentheses. Superscripts a, b, c, d, and e indicate significance at the 1, 5, 10, 15, and 25% levels, respectively.
a typical Soviet high-rise house.7 The relative floor variable is defined as the floor on which the flat exists divided by the total number of floors in the building. Consequently, the variable is an indicator of the relative height of the flat’s location within a building. A dichotomous variable indicating that the flat is on the top floor of the building is also included. Coefficient estimates reveal that top floor flats are discounted, although not significantly in this case. The reason is that in a Soviet-style high-rise apartment building, the owners of top floor apartments are solely responsible for roof leaks. There is no concept of a condominium association yet in Moldova. The relative floor variable coefficient estimate indicates that flats on higher floors are worth more, other things being equal. Location within the city clearly affects house prices. Recalling that the Center variable is the left-out variable, the estimated coefficients on the location variables indicate that prices are lower outside of the center district. Homes in the districts of Bubuieci, Durlesti, Posta Vecha, and the Telecenter are all worth significantly 7 A building story variable was also included in a preliminary version of the model in order to capture housing vintage. Residents of the FSU often refer to their homes as Stalin, Kruschev, or Breshnev homes reflecting the age and construction type. This variable was not significant, however, and was dropped from the model.
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less than comparable homes in the central district of the city. Houses in the other districts of Botanica, Buicani, and Riscani have prices that are not significantly different from those in the center, other things being equal. This evidence is consistent with that of Daniell and Struyk (1997) for Moscow showing that central district homes have sales prices that are much higher than those in second belt and remote districts of the city. Tiraspol Model For the Tiraspol model, we have asking prices of homes in logarithmic form as the dependent variable and descriptors of physical characteristics along with location variables as independent variables. A sample of data was obtained from this housing market from homes advertised in the newspaper. Asking prices were obtained, along with physical and location characteristics of the houses. Table I reports descriptive statistics while Table II reports the results of estimation. The typical home in this sample is a two-room flat with 53 square meters of total area. The mean asking price is $7,053. Model estimates reveal that three of the physical characteristic variables are highly significant: total area, total area squared, and the top floor variable. As with the Chisinau model, the price of flats rises with total area at a decreasing rate. The top floor variable is also highly significant in this model, reducing the house price, other things being equal. As for the relative floor variable, it is not significant, indicating that relative position within the building does not matter, unless the flat is on the top floor. There are four location variables included in the model and one omitted location variable. All four of the location variables are negative and highly significant. Since all four coefficient estimates are negative we have a clear indication that homes in the central district of the city command higher asking prices. Here again, we have evidence that location is a very important factor in determining house prices. This simple model of asking prices explains 88.18% of the variation in log asking prices observed in the sample. Consequently, we know that despite the institutional limitations of no mortgage market, no multiple listing service, and no official cadastre, there is still an amazing amount of rationality to the housing market. Asking prices of homes in this city follow very predictable patterns. Of course, the higher explanatory power of this model, as compared to the Chisinau model, is due in part to the difference in the dependent variables. It is easier to explain asking prices in the Tiraspol model than actual sales prices in the Chisinau model. 5. SUMMARY AND CONCLUSIONS Models of housing prices presented in this paper provide clear evidence of market forces in two principal cities of the transition economy of Moldova. In
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both cases, a relatively small set of independent variables describing both physical and location characteristics is capable of explaining a large proportion of the observed variation in prices. Factors found to be most important explanatory variables include total living area, top floor location in a high-rise building, and district location within the city. In both cities investigated, house prices are highest in the center district relative to all other districts. Simple hedonic models confirm that the same market forces that are observed in housing markets in market-oriented cities seem to be at work in these transition economy cities as well. In this sense, housing markets here appear to be quite similar to those in cities where market forces have been relied upon to allocate the housing stock for a long period of time. It is quite remarkable that such forces should be so clearly observed amid the confused and chaotic conditions of an economy relying on old central planning mechanisms, new market mechanisms, and elements of corruption and crony capitalism. The implications of such obvious market influence on housing markets in a transition economy include a number of important issues. First, the role of emerging mortgage markets, insurance, and the development of the legal system will facilitate the working of the housing market immensely. These institutional developments will make the fledgling housing market take off and result in market forces being even more powerful in the allocation of housing resources. Second, the emerging housing market means that development of both the legal and fiscal cadastres is of critical importance. The legal cadastre is necessary in order to define property rights properly. Beyond that, the fiscal cadastre in necessary in order to provide a tax base for newly created fiscally autonomous local governments. Third, the very shape of post-Soviet cities will undergo dramatic changes as market forces work to allocate real estate resources. The typical Soviet city with low-density center and high-density periphery will change as market forces make it clear that central location is valuable. Scarce locations in the center will be bid up relative to outlying locations. Consequently, the density gradient will be profoundly changed with the coming of the market. Bertaud and Renaud (1997) report that in Russia the price gradient switched from being positive at the end of the Soviet era to being negative early after independence. These results from Moldova indicate that after nearly a decade of independence a negative price gradient has been clearly established. REFERENCES Alexeev, M. (1988a). “Market vs. Rationing: The Case of Soviet Housing,” Rev. Econ. Statist. 70(3), 414–420. Alexeev, M. (1988b). “The Effect of Housing Allocation on Social Inequality: A Soviet Perspective,” J. Comp. Economics 12(2), 228–234. Atkinson, A. T., and Micklewright, J. (1992). Economic Transformation in Eastern Europe and the Distribution of Income. Cambridge Univ. Press, Cambridge, UK.
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Bertaud, A., and Renaud, B. (1997). “Socialist Cities without Land Markets,” J. Urban Econ. 41(1), 137–151. Buckley, R., and Gurenko, E. (1998). “Housing Demand in Russia: Rationing and Reform,” Econ. Transition 6(1), 197–209. Daniell, J., and Struyk, R. (1997). “The Evolving Housing Market in Moscow: Indicators of Housing Reform,” Urban Stud. 34, 235–54. de Melo, M., and Ofer, G. (1999). “The Russian City in Transition: The First Six Years in Ten Volga Capitals.” Development Research Group, World Bank, Washington, D.C. Guzanova, A. K. (1997). “The Housing Market in the Russian Federation: Privatization and Its Implications for Market Development,” unpublished manuscript. Hacker, R. S. (1999). “The Effect of Residential Crowding on Labor Productivity with Evidence from the Twilight of Polish Socialism,” Real Estate Econ. 27, 135–167. Lanjouw, P. Milanovic, B., and Paternostro, S. (1998). “Economies of Scale and Poverty: The Impact of Relative Price Shifts During Economic Transition.” Development Economics Research Group, World Bank. Malpezzi, S. (1990). “Urban Housing and Financial Markets: Some International Comparisons,” Urban Stud. 27, 971–1002. Svejnar, J. (1991). “Microeconomic Issues in the Transition to a Market Economy,” J. Econ. Lit. 5, 120–138.
Emerging Housing Markets in Moldova John E. Anderson1 Department of Economics, University of Nebraska, Lincoln, Nebraska 68588 E-mail: [email protected] Received December 12, 2000 This paper provides tentative evidence on the extent to which market forces are now responsible of the determination of housing prices in the two principle cities of Moldova, a former Soviet republic. Microlevel data for flats in the two principal cities of Chisinau and Tiraspol are used to estimate hedonic price equations in an attempt to discern the extent to which market forces are now determining prices. Despite the fact that Moldova is taking a rather slow approach to economic transition in general, with the economy in a continued decline with GDP per capita falling, these data reveal a substantial degree of housing market rationality based on market forces. 䉷 2001 Elsevier Science Key Words: housing markets; economic transition; hedonic prices. Journal of Economic Literature Classification Numbers: R1, R5, H7.
1. INTRODUCTION The extensive housing stock in countries of the former Soviet Union (FSU) has undergone and continues to undergo privatization, with the extent varying substantially from country to country. Allocation mechanisms used for housing bore no resemblance to market forces in the past, with central planning ignoring the information that would be contained in prices. With independence, however, most countries of the FSU have privatized at least some housing and now rely on market forces, at least partially, to allocate resources in the housing sector. This paper examines the extent to which market forces are now responsible for the determination of housing prices and explains what implications follow from the reliance on market forces. Analysis of data drawn from the emerging housing market in Moldova over the period 1998–1999 is presented in the paper. Moldova has made good progress in privatizing the Soviet housing stock and most families now own their own flats. Microlevel data for flats in the capital city, Chisinau, with a population of nearly one million, and Tiraspol, a major industrial city in the break-away region 1
The author served as tax policy advisor on the USAID Fiscal Reform Project and the Local Government Reform Project in Moldova since 1998. The opinions expressed in this paper are those of the author alone, however, and should not be construed as those of USAID, KPMG Barents Group, the government of Moldova, or any of its agencies. 419 1051-1377/01 $35.00 䉷 2001 Elsevier Science All rights reserved.
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JOHN E. ANDERSON
of Trans-Dneister, have been used to estimate hedonic price equations in an attempt to discern the extent to which market forces are now determining prices. Despite the fact that Moldova is taking a rather slow approach to economic transition in general, with the economy in a continued decline with GDP per capita falling, these data reveal a high degree of housing market rationality based on market forces. In fact, regression models based on physical characteristics and location information explain a high percentage of the variation in housing prices, revealing that forces are at work despite a good deal of noise in the system due to currency depreciation, exogenous shocks due to Russian economic events, and other factors. While the results reported in this paper must be considered tentative, given the small data sets and obvious data limitations, there is an encouraging degree of clear market rationality revealed in the hedonic equations. Market forces are beginning to work despite numerous institutional limitations.
2. PRIVATIZATION AND THE DEVELOPMENT OF HOUSING MARKETS Privatization of Housing in Transition Economies The situation prereform has been described by Svejnar (1991, p. 126) as follows: While most socialist countries permitted limited leasing and de facto ownership of land, a market for land was basically nonexistent. A real estate market has emerged in recent years, although most housing is still rented at controlled prices that are significantly below market equilibrium. Housing costs have constituted a relatively small fraction of consumer expenditures for most households, although a significant group of urban residents pay substantial rents for deregulated housing, in some countries through a black market. The maintenance of houses was generally poor, and considerable excess demand for housing existed at the subsidized rental prices. On the other hand, the system succeeded in avoiding blatant urban poverty.2
Alexeev (1988a, 1988b) provides evidence that in the later part of the Soviet era market forces were already beginning to replace administrative rationing in allocating scarce housing resources in Russia.3 Since independence there have been varying degrees of privatization among the FSU republics. While privatization has proceeded at different paces in each of the FSU republics, most observers would agree that the process is essentially completed in many republics, but is just over half finished in Russia, according to Guzanova (1997, p. 8). Once the housing stock is privatized, however, we must be concerned with 2 Another economic impact related to housing is the effect of crowding on labor productivity, as discussed in Hacker (1999). 3 See Buckley and Gurenko (1998) for a critique arguing that Russian households were not able to beat the system and that Alexeev’s income elasticity estimates are biased upward.
HOUSING MARKETS IN MOLDOVA
421
the establishment of a secondary market for homes. In particular, we are interested in knowing to what extent market mechanisms begin to work in the allocation of housing units. To what extent do the forces of supply and demand begin to manifest themselves among the noise observed in house prices? Since the process of transition involves very substantial changes in relative prices between private and public goods, there are important distributional implications to consider, as well.4 Transition may bring a growing share of expenditures on housing, for example, as noted by Lanjour et al. (1998). Guzanova (1997) found that in the Russian experience, privatization of housing has resulted in disparate effects on various population groups. Those most likely to have their flats privatized include pensioners and relatively well-off families. The pensioners are by far the larger group and are generally reluctant to sell their homes once they have been privatized. They are immobile and not likely to participate in housing transactions. The second and smaller group is composed of relatively well-off families, who can be expected to become active participants in the housing market. Her research also reveals that high-quality flats in city centers are much more likely to be privatized than other homes. Specifically, she finds that quality of construction and location are important determinants of the likelihood of privatization. Other factors that have a bearing on the decision to privatize include the demographic characteristics of the household, the value orientations and level of education of the household, and the income level of the household. Daniell and Struyk (1997) also provide early evidence on the development of housing markets in Russia. Their work emphasizes early policy reforms, including fundamental legal reforms, and assesses whether those reforms were effective in developing a market orientation in the housing sector. Using longitudinal data they track private ownership, residential mobility, housing conditions, and housing affordability. They demonstrate that progress was clearly made in moving to functioning housing markets during the early years of independence. Privatization of Housing in Moldova Moldova is a small country and former Soviet republic west of Ukraine and east of Romania that has some 4.5 million residents. Independence from the USSR came in 1991, but bitter rivalries between ethnic Romanians and ethnic Russians complicated by the presence of the Soviet 14th army in the eastern part of the country resulted in a civil war during 1992–1993. The small breakaway region east of the Nistru River, called Transdneister, declared independence itself, but has not been recognized as a sovereign state by any other state. An uneasy ceasefire has been maintained, but a political resolution to this problem has not yet been accomplished. 4 For estimates of the distribution of income in Eastern Europe, and impacts of economic transition, see Atkinson and Micklewright (1992).
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Privatization of the housing stock is nearly complete in Moldova, as the government moved quickly after independence to privatize housing units, both flats and detached houses. There was a substantial share of the rural village housing stock that was privately owned in the Soviet era in Moldova, due to the nature of communes and villages (often consisting of several communes). In villages and communes, families had for the most part built their own homes on state-owned land. The government recognized those homes as privately owned. After independence, homeowners were permitted to keep their homes and an extensive program of land privatization has been quite successful. The former collective farms, both kolkhozes and sovkhozes, have been or are currently in the process of being privatized. Each of the n workers on the collective farm is given title to 1/n of the crop land, orchard land, and vineyard land. A secondary market is just beginning to develop for land parcels that have been privatized. Data on market values of these properties are insufficient to permit modeling of prices. Early indications, however, reveal that market prices are below the old Soviet-era normative prices based on intricate fertility indices. Urban residents typically lived in Soviet-style high-rise apartment buildings. Distinct vintages of homes are discernable, ranging from Stalin houses to Khrushchev houses to more modern houses: After independence, families were given the opportunity to purchase the flat in which they lived at very low cost, practically giving the flats to families. As an aside, it is interesting to note the animosity of village dwellers toward city dwellers when the issue of property taxation is raised. Village dwellers think it is quite unfair that they should be asked to pay a property tax on their homes, since they built their homes themselves. They claim that city dwellers were given their homes and should therefore be asked to pay a property tax. The obvious fact that the city dwellers received housing as a form of implicit wage paid by the state enterprise for which they worked is lost in this view. It was common in the Soviet system for railroad workers, for example, to live in a high-rise complex built for them by the state. In some cases, state enterprise workers actually built high-rise apartment buildings themselves, which they then occupied. In the minds of Moldovan village people, however, there are fundamental differences in the manner in which housing was obtained that have a bearing on public policy. In Chisinau, the price per square meter for the median home was $363.64 in 1998–99, while in Tiraspol the median price was $220.34. These figures can be compared to the Moscow average price of $610 (fourth quarter of 1996) reported in Guzanova (1997, p.19).5 Lower prices in Moldova are to be expected, since these Moldova cities are smaller than Moscow and the income level of the population is lower. Within Moldova, the higher price per square meter in Chisinau is also consistent with expectations, since Chisinau is the largest city in the country and is responsible for producing a large share of the country’s GDP. 5
For a detailed view of the experience of Russian cities in transition, see de Melo and Ofer (1999).
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Chisinau Housing Market Chisinau is the capital city of Moldova, home to some 800,000 residents. It is also home to most of the country’s business activity, generating a large share of Moldova’s GDP. The city is organized into eight districts, spread over the geographic area settled. The housing stock of Chisinau consists primarily of soviet-era high-rise homes, or apartment buildings. In addition, there is a substantial core of detached single family homes as well, primarily located in the Center and Tele Center districts, and in the historic district of Posta Vecha. With nearly all housing units privatized since independence, an active real estate market has emerged in Chisinau. Flats and detached homes are bought and sold, with and without the assistance of real estate brokers. A number of brokerage services have sprung up, with intense competition among them for listings. In fact, the sense of competition is so intense that there is no cooperation among brokers. Listings are treated as proprietary and there is no multiple listing service. Tiraspol Housing Market Tiraspol is a major industrial city in the Transdneister region of Moldova, east of the Nistru River. It is the home of the nation’s major industrial enterprises and electrical generation facilities, as well as of former Soviet military installations. This region is ideologically tied more closely to Soviet-era central planning methods of allocation rather than to market forces. Hence, one might expect that markets would not be used or permitted to allocate resources to such a great extent in this region. At a practical level, however, this region functions as one large free trade zone, with alleged traffic in all kinds of commodities, including weapons, drugs, and humans. From this point of view, it may well be the case that market forces are even freer to operate in this region than elsewhere in the country. 3. MODELS OF HOUSE PRICES Simple hedonic models are estimated for Chisinau and Tiraspol, with both physical characteristics and location characteristics used as explanatory variables. Similar models are estimated for both cities in order to illustrate the economic forces at work determining house prices and also to facilitate comparison of the results. Both samples are small and the results reported can only be considered preliminary, pending further research with more elaborate models and more comprehensive data. Chisinau Model The Chisinau sample includes observations on homes sold in 1999, ranging in price from $2,850 to $15,500. The average sale price was $9,845. Home size
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JOHN E. ANDERSON TABLE I Descriptive Statistics Chisinau Sample (n ⫽ 52)
Tiraspol Sample (n ⫽ 80)
Variable
Mean
Standard error
Variable
Mean
Standard error
Price ($) Log of price Total area Total area squared Rooms Relative floor Top floor Botanica Bubuieci Buicani Durlesti Posta Vecha Riscani Tele Center
9,845 9.1459 44.0577 2,008.635 1.7115 0.5873 0.1346 0.3654 0.0192 0.2500 0.0192 0.0577 0.0962 0.0577
2,854 0.3359 8.2993 689.1732 0.5475 0.2894 0.3446 0.4862 0.1387 0.4372 0.1387 0.2354 0.2977 0.2354
Asking price ($) Log of asking price Total area Total area squared Rooms Relative floor Top floor Balca Borodinca Kirov Krkazar
7,053 8.7756 53.1550 3,042.175 2.2250 0.5984 0.2250 0.3375 0.2125 0.0500 0.1250
2,749 0.4400 14.8143 1,563.535 0.7287 0.3029 0.4202 0.4758 0.4117 0.2193 0.3328
was 44 square meters of living space, on average, including 1.7 rooms. Table I provides descriptive. The data set consists of both sales prices and appraisals by professional real estate agents.6 Coefficient estimates for a simple hedonic model are presented in Table II. The dependent variable is the natural logarithm of the house price. Explanatory variables include measures of the size of the housing unit, its position within the building, and location within the city (by district). This model explains 69.52% of the variation in the log of price, indicating that a few objective variables can account for a large percentage of the observed variation in price. Despite all the limitations on housing market development, such as the lack of a mortgage market, there is a strong degree of rationality in prices. Total area and its square are both significant explanatory variables in this model. The positive sign on the total area variable and the negative sign on its square indicate that price rises with area at a declining rate. The number of rooms is only weakly significant, indicating that once area and its square are taken into account, the number of rooms in the home does not affect price very much. While flats in Moldova are always referred to by the number of rooms, for example a one-room or two-room flat, this designation apparently signals the overall size of the flat, not primarily the number of rooms into which it is divided. Two variables are included in the model to pick up effects of location within 6 Statistical tests indicate that the appraisal data do not differ significantly from the sales data in the reported hedonic equations.
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HOUSING MARKETS IN MOLDOVA TABLE II House Price Models Chisinau Model Variable Constant Total area Total area squared Rooms Relative floor Top floor Botanica Bubuieci Buicani Durlesti Posta Vecha Riscani Tele Center N R2 F Log likelihood
Tiraspol Model
Coefficient Standard error a
6.4079 0.1034a ⫺0.0010a 0.1155e 0.2884b ⫺0.1132 ⫺0.0863 ⫺1.1794a ⫺0.1130 ⫺0.4172a ⫺0.3533a 0.0050 ⫺0.1979c 52 0.6952 10.6924 21.3159
0.6359 0.0320 0.0004 0.0932 0.1205 0.1076 0.0970 0.1325 0.0876 0.1294 0.1004 0.1042 0.1072
Variable Constant Total area Total area squared Rooms Relative floor Top floor Balca Borodinca Kirov Krkazar
n R2 F Log likelihood
Coefficient Standard error 6.6589a 0.0619a ⫺0.0004a 0.0267 0.0504 ⫺0.1712a ⫺0.1561a ⫺0.1355a ⫺0.4653a ⫺0.1474a
0.3266 0.0131 0.0001 0.0614 0.0747 0.0639 0.0467 0.0543 0.0999 0.0516
80 0.8818 66.4732 42.9144
Note. Cells list coefficients, with standard errors in parentheses. Superscripts a, b, c, d, and e indicate significance at the 1, 5, 10, 15, and 25% levels, respectively.
a typical Soviet high-rise house.7 The relative floor variable is defined as the floor on which the flat exists divided by the total number of floors in the building. Consequently, the variable is an indicator of the relative height of the flat’s location within a building. A dichotomous variable indicating that the flat is on the top floor of the building is also included. Coefficient estimates reveal that top floor flats are discounted, although not significantly in this case. The reason is that in a Soviet-style high-rise apartment building, the owners of top floor apartments are solely responsible for roof leaks. There is no concept of a condominium association yet in Moldova. The relative floor variable coefficient estimate indicates that flats on higher floors are worth more, other things being equal. Location within the city clearly affects house prices. Recalling that the Center variable is the left-out variable, the estimated coefficients on the location variables indicate that prices are lower outside of the center district. Homes in the districts of Bubuieci, Durlesti, Posta Vecha, and the Telecenter are all worth significantly 7 A building story variable was also included in a preliminary version of the model in order to capture housing vintage. Residents of the FSU often refer to their homes as Stalin, Kruschev, or Breshnev homes reflecting the age and construction type. This variable was not significant, however, and was dropped from the model.
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less than comparable homes in the central district of the city. Houses in the other districts of Botanica, Buicani, and Riscani have prices that are not significantly different from those in the center, other things being equal. This evidence is consistent with that of Daniell and Struyk (1997) for Moscow showing that central district homes have sales prices that are much higher than those in second belt and remote districts of the city. Tiraspol Model For the Tiraspol model, we have asking prices of homes in logarithmic form as the dependent variable and descriptors of physical characteristics along with location variables as independent variables. A sample of data was obtained from this housing market from homes advertised in the newspaper. Asking prices were obtained, along with physical and location characteristics of the houses. Table I reports descriptive statistics while Table II reports the results of estimation. The typical home in this sample is a two-room flat with 53 square meters of total area. The mean asking price is $7,053. Model estimates reveal that three of the physical characteristic variables are highly significant: total area, total area squared, and the top floor variable. As with the Chisinau model, the price of flats rises with total area at a decreasing rate. The top floor variable is also highly significant in this model, reducing the house price, other things being equal. As for the relative floor variable, it is not significant, indicating that relative position within the building does not matter, unless the flat is on the top floor. There are four location variables included in the model and one omitted location variable. All four of the location variables are negative and highly significant. Since all four coefficient estimates are negative we have a clear indication that homes in the central district of the city command higher asking prices. Here again, we have evidence that location is a very important factor in determining house prices. This simple model of asking prices explains 88.18% of the variation in log asking prices observed in the sample. Consequently, we know that despite the institutional limitations of no mortgage market, no multiple listing service, and no official cadastre, there is still an amazing amount of rationality to the housing market. Asking prices of homes in this city follow very predictable patterns. Of course, the higher explanatory power of this model, as compared to the Chisinau model, is due in part to the difference in the dependent variables. It is easier to explain asking prices in the Tiraspol model than actual sales prices in the Chisinau model. 5. SUMMARY AND CONCLUSIONS Models of housing prices presented in this paper provide clear evidence of market forces in two principal cities of the transition economy of Moldova. In
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both cases, a relatively small set of independent variables describing both physical and location characteristics is capable of explaining a large proportion of the observed variation in prices. Factors found to be most important explanatory variables include total living area, top floor location in a high-rise building, and district location within the city. In both cities investigated, house prices are highest in the center district relative to all other districts. Simple hedonic models confirm that the same market forces that are observed in housing markets in market-oriented cities seem to be at work in these transition economy cities as well. In this sense, housing markets here appear to be quite similar to those in cities where market forces have been relied upon to allocate the housing stock for a long period of time. It is quite remarkable that such forces should be so clearly observed amid the confused and chaotic conditions of an economy relying on old central planning mechanisms, new market mechanisms, and elements of corruption and crony capitalism. The implications of such obvious market influence on housing markets in a transition economy include a number of important issues. First, the role of emerging mortgage markets, insurance, and the development of the legal system will facilitate the working of the housing market immensely. These institutional developments will make the fledgling housing market take off and result in market forces being even more powerful in the allocation of housing resources. Second, the emerging housing market means that development of both the legal and fiscal cadastres is of critical importance. The legal cadastre is necessary in order to define property rights properly. Beyond that, the fiscal cadastre in necessary in order to provide a tax base for newly created fiscally autonomous local governments. Third, the very shape of post-Soviet cities will undergo dramatic changes as market forces work to allocate real estate resources. The typical Soviet city with low-density center and high-density periphery will change as market forces make it clear that central location is valuable. Scarce locations in the center will be bid up relative to outlying locations. Consequently, the density gradient will be profoundly changed with the coming of the market. Bertaud and Renaud (1997) report that in Russia the price gradient switched from being positive at the end of the Soviet era to being negative early after independence. These results from Moldova indicate that after nearly a decade of independence a negative price gradient has been clearly established. REFERENCES Alexeev, M. (1988a). “Market vs. Rationing: The Case of Soviet Housing,” Rev. Econ. Statist. 70(3), 414–420. Alexeev, M. (1988b). “The Effect of Housing Allocation on Social Inequality: A Soviet Perspective,” J. Comp. Economics 12(2), 228–234. Atkinson, A. T., and Micklewright, J. (1992). Economic Transformation in Eastern Europe and the Distribution of Income. Cambridge Univ. Press, Cambridge, UK.
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Bertaud, A., and Renaud, B. (1997). “Socialist Cities without Land Markets,” J. Urban Econ. 41(1), 137–151. Buckley, R., and Gurenko, E. (1998). “Housing Demand in Russia: Rationing and Reform,” Econ. Transition 6(1), 197–209. Daniell, J., and Struyk, R. (1997). “The Evolving Housing Market in Moscow: Indicators of Housing Reform,” Urban Stud. 34, 235–54. de Melo, M., and Ofer, G. (1999). “The Russian City in Transition: The First Six Years in Ten Volga Capitals.” Development Research Group, World Bank, Washington, D.C. Guzanova, A. K. (1997). “The Housing Market in the Russian Federation: Privatization and Its Implications for Market Development,” unpublished manuscript. Hacker, R. S. (1999). “The Effect of Residential Crowding on Labor Productivity with Evidence from the Twilight of Polish Socialism,” Real Estate Econ. 27, 135–167. Lanjouw, P. Milanovic, B., and Paternostro, S. (1998). “Economies of Scale and Poverty: The Impact of Relative Price Shifts During Economic Transition.” Development Economics Research Group, World Bank. Malpezzi, S. (1990). “Urban Housing and Financial Markets: Some International Comparisons,” Urban Stud. 27, 971–1002. Svejnar, J. (1991). “Microeconomic Issues in the Transition to a Market Economy,” J. Econ. Lit. 5, 120–138.