Tag: Moscow

How Transport Links Help Market Integration: the Case of Moscow Office Rental Market

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This brief is based on a research project on the Moscow office real estate (Ignatenko & Mikhailova, 2014). We study the market for office space rentals in Moscow. Our main interest regards spatial competition: when an object is rented, does the rental rate respond to the behavior of competing objects in a geographical vicinity? What is the geographical extent of the market, and how do urban transportation links help integrate local markets and extend the geographical scope of competition?  We find that urban transportation “shortens” the effective distances and intensifies competition between geographically differentiated objects. The effects are modest but statistically significant.

We analyze a unique dataset on office space rental deals in Moscow in 2001-2010. The dataset was collected by an analyst team at Cushman & Wakefield Russia and includes all the deals on office spaces that were publicly advertised, with detailed and verified information on the object characteristics, rental prices, and the contract dates.  We also have information on the object’s location – precise geographical coordinates – and thus we are able to study this market at a very detailed level of geographical aggregation.

Moscow Office Rental Market in 2001-2010, an Overview

The market for office space in Moscow went through a stage of rapid growth through 1990s and 2000s. Economic development drove the demand for all types of offices at all price ranges. The demand was met by a conversion of residential and industrial spaces into offices, as well as by new construction.  In our sample, the top year in terms of the number of transactions was 2005, with a slight decline in the years after, and a somewhat sharper drop in 2009 after the global financial crisis. The composition of different types of offices and their characteristics have changed toward slightly higher quality through that decade:  the share of transactions with class A and B+ offices was steadily rising (see Figure 1).

Figure 1. Number of Office Rental Transactions by Year and Class of Office

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Source: Authors’ own calculations.

Up until the third quarter of 2008, the rental rates were constantly increasing. Average office rental prices in Moscow grew more than two-fold during 2001-2008, but fell almost to the initial level after the global financial crisis and the subsequent crush of the market. Figure 2 illustrates the quarterly index of simple average office rental rates and the corresponding hedonic price index. A hedonic index is constructed using a regression of the objects’ prices onto the observed characteristics of the objects and a set of time period indicators. Thus, the regression decomposes the overall price into the contributions of object quality and time period. The estimated time effects give the hedonic index, cleaning the time series of prices from all of the effects of changes in quality. Interestingly enough, the value of the hedonic index at the beginning of 2010 was exactly at the same level as in 2001. Thus, although the average price level was higher in 2010, all the price gains can be attributed to an increase of the average object’s quality.

Figure 2. Average Price and Hedonic Price Index of Moscow Office Rentals, 2001-2010

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Source: Authors’ own calculations.

In Moscow we observe a typical behavior of the real estate market during booms and busts. While prices rise, tenants switch to lower quality objects to fit the budget, and the hedonic index rises faster than the average price.  When prices fall, tenants support the higher end of market, looking for high-quality bargains, and the hedonic index falls faster than the average price.  Overall, Moscow real estate market fits the basic stylized facts.

A hedonic analysis reveals the value of the object’s characteristics in the eyes of the consumer. The presence of transport infrastructure creates direct benefits. Consumers value an accessible transport infrastructure: offices lose 9% of rental price for each 10 minutes of walking distance to the nearest subway station. It is easy to calculate the surplus from a new subway line: it would increase the value of the land and real estate objects in the area of service. Because land and real estate are supplied inelastically, the bulk of this benefit goes to the owner. Consumers (in our case, tenants) receive the benefit of shorter commuting time, but in exchange for higher rental prices.

In addition to these direct benefits, transport links also tend to promote market integration by making objects that are near and objects that are far away, more substitutable in the eyes of the consumer. Transport links lower the degree of product differentiation in the geographical dimension. And, as with any kind of product differentiation, this should limit seller’s market power and reduce prices.  The benefits of increased competition (if any) go directly to consumers. We analyze competition between the offices for rent in the context of geographical distance to determine whether transport links indeed make competition stronger.

Spatial Competition and Transport Infrastructure

We use the dataset to study price competition between real estate objects.  Real estate objects are best thought of as differentiated goods. Each object possesses a set of characteristics and a fixed location, i.e. objects are differentiated by consumer characteristics and by geography. Each object is essentially unique, but the owners’ market power is limited by competition. Competition between objects is stronger if objects are closer in consumer characteristics and in location, so that potential tenants view them as closer substitutes. An owner of an object reacts to the behavior of their competitors, i.e. sets the price reacting to the prices set by similar objects in the neighborhood. We study how the strength of price reaction depends on geographical distance between objects by estimating the slope of the reaction function of the owners in a price competition game.

Our estimates show that price reactions of competition from the neighboring objects are very modest. Hypothetically, if  two offices of similar size in the same location are for rent, and one of them cuts a price by 10%, the other responds on average by cutting price by only 1.7%. Even at a zero geographical distance between competing objects, there is substantial market power, presumably because of strong differentiation in the other product characteristics. The response is weaker if competing objects are located further away from each other, and at 1.8 kilometers is statistically indistinguishable from zero, i.e. such objects practically do not compete.

When we consider competition inside a more narrowly defined class of offices (grouping A and B+ offices vs B- and C offices), the results change slightly. We find that offices compete mainly within their own class. The reaction to the prices of another class is not different from zero, even in the immediate geographical vicinity. For the offices within the same class the geographical range of competition extends from 1.8 km to 2.1 km, and the reaction to neighbor’s prices is slightly stronger, with an elasticity of 0.2.

As a next step, we include transport links into our measure of distance. Consider offices that are located on the same subway line, i.e. where a passenger can travel between locations without changing the line. Price response to such competing objects is not much stronger: about 22% of the shock, but it stays above zero at longer distances. Price responses become indistinguishable from zero only at a distance of about 4.7 km. Figure 3 compares the two estimated price response functions: for all offices and for offices of the same class and on the same subway line.

Figure 3. Price Response as a Function of Geographical Distance when Objects are Connected by a Direct Subway Line

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Source: Authors’ own calculations.

To summarize, our findings confirm the old stylized fact: the real estate market is very “local”. It is local not only in a geographical sense, but also in a product space sense: objects compete only with similar objects and mainly in the immediate geographical neighborhood.  Direct transportation links (subway) promote market integration: it “shortens” the effective distance and makes the geographical boundaries of a market much wider. In the case of office real estate, the effect on the price level is very modest. The price reaction is weak even in the immediate vicinity, and it decays quickly with the distance. Yet our research underscores that the effects of transportation links on market integration and competition are real and measureable, and should be considered in cost-benefit analysis of transportation projects.

References

Ignatenko, Anna and Tatiana Mikhailova “Spatial Competition and Transport Infrastructure: The Case of Moscow Office Rental Market”, mimeo, 2014

Presidential Elections in Russia: Massive Vote Fraud Ensures that Legitimacy is in Doubt, but the Policy Direction is not

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The March 4th, 2012, elections formally returned Vladimir Putin, the paramount leader of Russia since 1999, to the presidency. Despite Draconian restrictions on entry, financing, campaigning by other candidates, Putin’s dominance of TV, blatant use of state employees and funds to his own advantage, and significant vote fraud, the victory was underwhelming in the end. While the official tally was only 63.6 percent in Putin’s favor, estimates of his vote share by independent observers relying on networks of tens of thousands of volunteers were in the range of 49-57 percent of the turnout; even lower.  (If his share was truly below 50 percent, a run-off vote would have to take place between Putin and the runner up) The second major outcome of the elections was the successful attempt by civic society to ensure a fair vote count in Russia’s largest city and capital, Moscow, where Putin’s official vote share (45 percent) on March 4th was the same that United Russia achieved in the December 4th parliamentary elections. (Generally, Putin polls much higher than United Russia.) The third outcome was the emergence of Mikhail Prokhorov, a billionaire with negligible experience in politics, as a major political force representing large cities and young educated voters.

The Success of Civic Society in Moscow and Vote Fraud Elsewhere

The central issue in the wake of the March 4th elections is the extent of fraud organized by the incumbent. Massive fraud during the December 4th parliamentary elections generated mass protests in response. In total, hundreds of thousands of Muscovites took part in four large rallies held during this winter. (No political rallies of comparable size, except for the state-sponsored pro-Putin ones, have taken place during the last 15 years.) A similar discrepancy between the actual vote and official returns was expected to generate even larger protests this time round.

Despite dozens of reported and video-documented cases of organized groups brought in to Moscow to vote multiple times and the presence of tens of thousands of observers, public outrage after massive vote fraud in the parliamentary elections last December is likely to have prevented the most outrageous and blatant forms of fraud during these elections. No less important, it is also likely that they generated less directly observable forms of electoral manipulation. Not surprisingly, for Moscow, the vote count by Citizen Observer, Golos, and other independent and highly respected observer organizations nearly coincided with the official election results, certified by the widely despised Central Election Commission (CEC). (Since December, the name of the head of CEC, Vladimir Churov, has become a synonym for incompetence and of fawning loyalty to the incumbent.) This does not mean, however, that no fraud took place outside the capital.

Figure 1. Cross-plot of the United Russia (Putin) vote share vs. turnout in the December 4, 2011, parliamentary elections and the March 4, 2011, presidential elections in Moscow. (Courtesy of Alexei Zakharov, HSE and Citizen Observer, using the CEC data.)


A side effect of the fair vote count on March 4th, 2012, in Moscow was that it highlighted the extensive centrally-organized fraud in parliamentary elections held on December 4th, 2011. (See the December 2011 issue of the FREE Policy Brief for a snap analysis of the parliamentary elections.) Figure 1 shows that the suspicious-looking relationship between the turnout and the Putin-led United Russia Party, highly visible in December (top figure), completely disappeared in March (bottom figure). Thus, the strong correlation between turnout and the United Russia vote share is a result of ballot-stuffing rather than anything else (theoretically, such a correlation might be caused by some socio-demographic characteristics of United Russia’s supporters). Similarly, Figure 2 exhibits a “normal” (Gaussian) distribution of total votes for United Russia/Putin by turnout (this is what should be expected theoretically, and is consistently observed in democratic elections around the world) on March 4th (bottom figure) and an unusual distribution, a result of changed voting protocols on December 4th (top figure).

Figure 2. Number of ballots by turnout in the December 4, 2011, parliamentary elections, and the March 4, 2011, presidential elections in Moscow. (Courtesy of Maxim Pshenichnikov using the CEC data.) Note the spikes on 70,75,70,85, and 90 percentiles on the left graph, a result of “targeting” by election officials. 

Outside Moscow, the situation was different. Across the country, independent observers documented ballot stuffing and manipulation of local vote returns. St. Petersburg, the second largest city in Russia with a population of just over 4 million and the cradle of the “Putin’s team”, is a case in point. The preliminary estimates, based on a (nearly random for these purposes) sample of 269 polling stations (which is about 12 percent of the total number of station in the city), shows that the actual vote share for Putin was 50 percent rather than the officially reported 65 percent, while for Prokhorov it was 22 percent instead of 14 percent, and for Zyuganov 15 percent instead of 11 percent in the official tally. These estimates are based on the comparison between the official results as certified by the Central Electoral Commission with official copies of vote protocols signed by accredited observers and members of local electoral commissions at the polling stations. In other words, the discrepancy is a result of vote fraud at the level of the territorial electoral commission instead of more conventional forms of fraud, such ballot-stuffing at polling stations.

New Faces of Russian Politics

Three of the four competitors against Putin on March 4th were veterans of Russian politics. The Communist party Chairman, Gennady Zyuganov, lost presidential elections to Boris Yeltsin in 1996, Putin himself in 2000, and to Dmitry Medvedev, Putin’s figurehead “heir,” in 2008. (In 2004, the communists ran a minor candidate). Vladimir Zhirinovsky, a perennial nationalist candidate for presidency since 1991, has maintained a parliamentary faction for his one-man party for 20 years, but has never come close to winning the presidency. Sergei Mironov, a former Putin ally (in 2004 he ran for presidency with the announced goal “to help Putin win presidency”), was the main beneficiary of the December 4th, 2011, vote when many people supported his party primarily for the reason that parties they would have otherwise voted for were banned from participation. By official tally, Zyuganov got 17.2 percent (2nd place), Zhirinovsky 6.2 percent (4th place), and Mironov 3.9 percent (5th place). Despite the fact that these three have been on the ballot for a long time, they have never succeeded in presenting a genuine alternative choice for Russian voters at the polls and therefore posed no serious threat to Putin’s authority.

Mikhail Prokhorov, the 2nd richest person in Russia according to Forbes, ran a campaign that was watched warily by both Putin in Kremlin and Putin’s opponents in the liberal camp, and came in 3rd place with an official total of 8.0 percent. In Moscow, his result was even more impressive with 22 percent of the vote, second only to Putin’s 45 percent. While Prokhorov certainly benefited from the absence of Grigory Yavlinsky, who failed to clear the (unheard of in democratic countries) requirement to collect 2 000 000 signatures, and other liberal politicians, his results exceeded the previous combined returns of the liberal parties and candidates in parliamentary and presidential elections in 2000. The success of his candidacy have raised doubts on a long-held assumption in Russian politics that a rich, not to mention very rich, candidate has no chance of gaining traction in popular vote.

Another new face in Russian politics, Alexei Navalny has a law degree, business background, and was a member of the leadership in the Yabloko party (expelled in 2007) before becoming a famous blogger and shareholder activist in the beginning of 2010.  His blog (navalny.livejournal.com) is now one of the most popular blogs in Russia, with more than 66,000 followers. A major boost to its popularity was the “Rospil” project that focused on protecting minority shareholders of large state-owned companies (and, by extent, on the management of the taxpayers’ property by the Putin government). Navalny used his blog to organize large-scale petitioning and litigation campaigns related to corruption in state-controlled companies.  As a result of these activities, Navalny was described by the BBC in 2011 as “arguably the only major opposition figure to emerge in Russia in the past five years.”  (Obviously the BBC has not foreseen the rise of Prokhorov.) After December 4th, 2011, Navalny became a major leader of the protests and organizers of election observers.

“Staying the Course”

President-elect Vladimir Putin will start his new 6-year term in difficult times. The election raised questions about his true legitimate level of popular support, yet there is little doubt that he does not face any viable alternative challengers in the near future. Given that Putin has proven himself extremely rigid in the choice of policy and personnel (he would not get rid of close subordinates even if wide-spread corruption allegation would make them a visible drag on his popularity), the new government is not expected to be radically different from the current one (which features most of the ministers serving for 5-10 years in their current capacity). His anointed prime-minister is not a new face either. Dmitry Medvedev, who served as Russia’s president for the last 4 years, is not expected to bring forward any major policy changes.

Fortunately for Putin the opposition is not organized and cannot settle on any particular message or alternative policy direction, let alone viable leader. The protest movement during the winter of 2011-12 was characterized more by decentralized leadership, featuring a number of prominent literature, arts, and entertainment figures. With its goal to ensure fair elections, it has, however, united a very diverse group of smaller movements ranging from radical young communists to libertarians despite its not having provided an alternative leader to Putin.  In the end, the outcome of the March 2, 2012, presidential election has ended the myth of a significant Putin majority, casted considerable doubt on his legitimacy and has shown that Russians seem hungry for a change. It has, however, also left a big question mark on what the opposition’s next steps are and who the alternative could be.