I share here a preliminary analysis of the effects of the City of Buenos Aires rent law, enacted in 2017, on rental values. This law, declared unconstitutional in May of this year, freed the tenants from the payment of the real estate commission, while also imposing a maximum commission to be paid to the real estate companies. In particular, one of the issues that was discussed among those who questioned the law in the media, is that the measure would not have a positive effect on the tenants, since the owners, since then in charge of the cost of the commission, would transfer that cost to the value of the rent. The purpose of this post is to investigate that hypothesis, and in the way that could be verified in the data. The proposal here is the estimation of the effect as part of a model of rental values, following a methodology of the quasi-experimental type.

The methodology, the data, and the code (Python + Stata) are open in this project on github . This is an exercise in progress and in future posts I will surely add more results and estimators.

About the law

On September 8, 2017, the legislature of the City of Buenos Aires passed Law 5859 , which became effective on September 16 (more info in the news: Here , here ).

This law was sanctioned with the objective of benefiting the tenants. The law established, first, that the real estate commission would not be paid by the tenants, but by the owners. This modified what was usual practice, in which the tenant was charged with the cost. This would imply a reduction in the cost of entry to a rental contract for the tenants, since these in many cases used to pay a month, or more in terms of commission. In addition, the law established a maximum for this commission, corresponding to an extra month (equivalent to 4.15% -1 month over 24- of the total value of the contract) (Note: It was common to see higher commissions (1.5 or 2 months of rent)). The real estate agencies could not charge for other expenses, such as the costs of managing reports (conditions of ownership, liens and inhibitions). Finally, the law obliged all real estate agents to show a sign that warns of this new modality to tenants, on the points mentioned above, and appointed the Housing Institute of the City (IVC) as the person in charge of ensuring the rights of tenants and landlords, in conjunction with the City Ombudsman to provide free legal assistance.

Projects to a similar extent were discussed later in the Province of Buenos Aires 1 and nationally (see more here ), but so far has not been finalized a final sanction in these cases.

This year, on May 10, 2019, the Chamber of Administrative Litigation declared the rent law unconstitutional. (News: here and here) . The media suggests that the City Government will continue this legal dispute to keep the law in force.

On theoretical effects of the law

Consider first the transfer of commission payment to the owner and the argument that suggests that this measure will not have a positive effect on the tenants. Under this argument, the owners reacted by increasing the value of the rents, in order to neutralize the extra cost they have to face because of the law. Is this idea reasonable?

Indeed, such an argument could arise from a simple theoretical model of aggregate supply and demand. A simplified model of this type is shown below. The amounts of apartments demanded and offered for rent are represented according to the rental prices. If there were no commissions, and transactions could be made without intermediaries, the equilibrium would occur at the intersection of supply and demand curves. However, in the presence of the commissions, the rental market finds a balance in what the tenant disburses (in total), less the commission that the real estate company takes (let’s call it $C$ ), it will be what the owner receives. In the chart, the balance is defined by the prices $\overline{p}$, $\underline{p}$ and the amount of rented property $Q^*$. Moreover, in a classic scheme of this kind, the observation arises that, under normal conditions, it will not matter who falls behind the obligation to transfer the money from the commission to the real estate. The final charge of the commission will be shared between both parties of the market, depending on which party tolerates more the loss implied by the payment of the commission (ie, which curve is more inelastic).

In other words, under these classical assumptions, we could summarize the situation before and after transferring the obligation to pay the commission, according to the classical model, it could be summarized as follows:

For the purposes of the empirical analysis that interests us here, it is important to note that:

i) Following the transfer of the payment of tenants to owners, we should observe an increase in the prices offered by the owners, which is due to the incorporation of (part of) the commission to the price.

ii) The added well-being of the tenants ( 2) remains unchanged.

What would be the expected magnitude of the increase? In principle, since the rent is fixed during the 24-month period (plus the respective readjustments), then it is not reasonable that it be translated into an increase in the value of the monthly rent completely, but rather that the increase be distributed during the period. Rather than thinking that the commission will be transferred in 24 months, in the context of our economy, with its high real interest rate, it would be more reasonable to think that most of it is transferred to the first part of the contract.

Let’s now turn to the limitation of the amount of the commission to a maximum of the equivalent of 1 month’s rent. The effect I expect here will depend on what commission the tenants are paying, and it is expected to vary according to the market segment. The graph above suggests that if C is lower, then one of the consequences is that the price $overline {p}$ will be lower, (and $\underline {p}$ will be higher) with which the load transferred to the rental value It will be less. From this simple scheme then, we can infer that:

iii) The welfare of the tenants, and also that of the owners, will increase if the commission charged by the real estate companies is reduced. That is, if the limitation of the commission in this case (one month) involved a reduction in what the real estate agencies charged, part of the effect will result in a lower price to be paid by the tenants.

Identification Strategy Idea

The purpose now is the identification of the effect of the introduction of the law on rental values. This identification has the difficulty that affected the whole territory of the City of Buenos Aires, and if only the evolution of the average rent in CABA is observed, the effect could be confused with many other factors that affected the rents as a whole during the period of interest. For example, factors to take into account would be the level of inflation, (since contracts are mostly denominated in pesos), alterations in the exchange rate could have an effect on observed rental values, etc.

As a strategy, I propose to see the regulatory changes as a natural experiment, which altered the conditions of the rental market in the City of Buenos Aires, relative to the Province. The City and the Province taken as a whole, however, are hardly comparable. The main idea of identification here is based on exploiting the discontinuity offered by the boundary of the City with the Province of Buenos Aires. The City is surrounded by the Province, and there are rental properties on both sides of the City’s boundary, at least to a large extent. Moreover, the gradient of rental prices in the city suggests that, at least on average, there is a discount that is a function of the distance to the business center of the Capital. By taking housing that is close to the gradient, we make sure that your valuation will be similar. If the regular change introduced a change in the prices of CABA, then we should observe a discontinuity in that relation.

But even more, we should also bear in mind that there may have been a discontinuity in prices previously due to the change between Capital and Province. After all, there are multiple differences, for example, attributable to the way in which the territory is managed in the City and in the respective municipalities of the Province, and which could generate discontinuities in the price. What will be proposed as a strategy then, is that the discontinuity has changed after the introduction of the regulatory change.

For an introduction to regression discontinuity designs see, for example, Gertler et. a. 2011, Angrist and Pischke(2014). Some spatial applications are found in Hidano et al (2015), Egger and Lassman (2015).

A limitation of this strategy would be if the potential tenants, faced with the increase in prices in Capital, sought to rent in the Province. This would violate one of the assumptions under which this strategy is valid. However, it should also be noted that if this problem exists, the bias would tend to reduce the effect of interest, so if we observe an increase in the discontinuity it will be sufficient to verify the hypothesis.

Data

The data analyzed here comes from the open data of Properati . They refer to rental ads (offered values), and collected from the main online rental platforms. The data period covers 2016-2018, that is, one year and 8 months before the change and one year and 4 months after.

These offers were mapped and grouped into four groups, in order to have results for different sectors of the market.

Offers of rent in a buffer of 1000 meters in the limit of the City

Some statistics

The following are some descriptive statistics of the apartment rental offers in the period. The first variable in the table presents the value of the square meter in pesos, the second variable price_apro is the value of the rent in pesos, then logprice is the same price in logarithms. Delta is the distance to the limit (defined negative in the capital). Treatment is the dummy of CABA. Post indicates the period after regulatory change, and DD is an interaction that we will explain later.

* Extreme values were ruled out.

Econometric Estimation

The model of interest can be specified as follows:

$Y_ {i} = \beta_ {0} + \beta_ {1} \delta_ {i} + \beta_ {2} Post + \beta_ {3} CABA + \beta_ {4} Post * CABA + \epsilon_ {i}$

Where $Y_ {i}$ is the price of the offer, $delta_ {i}$ is the distance to the limit (defined negatively for capital direction distances) ,$Post$ is the dummy of the post-change period of the law, and $CABA$ is the dummy that points with 1 to CABA.

The parameter of main interest in this case is $beta_ {4}$ since it will indicate an increase in the discontinuity after the introduction of the law.

Starting with the rental value in m2, the base estimate is:

First, we can see that the existence of a gradient in prices is verified, just as we had hypothesized. The gradient is economically significant, representing 1 standard deviation for every 500 meters.

We can also see that once the gradient is taken into account, the model does not need to differentiate between CABA and Province.

The post variable shows the expected increase in prices, which could be a reflection of inflation.

Finally, the variable of interest, DD in this case shows that the discontinuity was enlarged after the law was enacted. In principle, this would corroborate the hypothesis of the transfer to the price.

The predictions of the model can be seen in the graph below:

Rental values per square meter

As an alternative to the previous specification, we also have the equation in logarithms:

The curious thing about this specification is that the negative difference in favor of the Province is maintained once the price gradient was incorporated. The conclusion about the effect of the regulation is also coincident with what was expected. In this case, the coefficient suggests an additional 10% increase that could be attributable to the change in regulation. While superior to what I had in mind, it is not out of what we had previously raised.

$Y_ {i} = \beta_ {0} + \beta_ {1} \delta_ {i} + \beta_ {2} Post + \gamma_ {j} \sum_{1}^{4}area_{j,i} + \beta_ {4} Post * CABA + \epsilon_ {i}$

Results by area

As we mentioned earlier when discussing the theory, the expected effects could present differences according to the specific conditions of the markets in question. In order to allow variability among the effects, we divided the sample into four areas:

Then, we generalize the econometric specifics, to allow specific effects by areas. The resulting estimate of the model in logarithms is:

We can see now, in the first place, that the effect reverses the sign for Area 1. I think that in this case we could be confusing the effect with a renewal of the important area that occurred in Vicente Lopez. For the remaining areas, we can see that the effect is maintained, increasing in Areas 2 (5%), 3 (15%) and 4 (18%).

Preliminary conclusions

The increase in the discontinuity of prices observed between Province and Capital seems to suggest that the owners increased their offer values, and this is consistent with the hypothesis that they transferred the commission to the rental contract. The magnitude of the effect found so far suggests that the transfer was important, especially in the south and southeast areas of the city limits.

Next steps

One question that may arise is how much this data applies to the generality of the City. Does this data constitute a representative sample? Clearly not, but the consideration of the different areas seems to be representative of different segments of the market. This is something that we can examine in a next post.

In terms of the modelling strategy, since we have data to do it, we could explicitly model the trends in the respective areas. We could also examine in a greater extent the implicit assumption of time constant discontinuity between the City and the Province.

Another effect that has been mentioned in the media, is that the measure could also have brought about an increase in the number of offers through direct owners. I do not have at the moment to see it, but it would be interesting to move in that direction.

Notes

1 In the Province of Buenos Aires, the project that eliminates commissions for tenants received a half sanction in December 2018. See more here

2 Measured by consumer surplus.