Hedonic regression model

I am writing my BA thesis in finance. I am doe with the first two chapters which are theoretical. I need last two chapters which include:

  

1. Research Methodology

1.1. Data Collection

1.2. Hedonic Regression Model

1.3. The Chow Test

1.4. The Variables

2. Data Analysis

2.1. Results

2.2. Regression Results

2.3. Rent level drivers in Amsterdam 

2.4.  Comparison between Amsterdam &Rotterdam 

 The paper is mostly a re-writing of another thesis. I will send the other thesis. However, you have to use different data for the regression model. 

Paper length: 3000 words (equally distributed between the 8 parts)

APA style

NO plagiarism: it has to be 100 % origianl

Deadline: 30 hours from now

TentativeOutline:

1. Introduction

1.1. The Dutch Rental Market

1.2. Research Method

1.3. Research Questions

1.4. Relevance of the research

1.5. Structure of the thesis

2. Literature Review

2.1. Dutch Housing Market

2.2. The Housing Market in Amsterdam

2.3. The Housing Market in Rotterdam

2.4. Previous Studies

3. Research Methodology

3.1. Data Collection

3.2. Hedonic Regression Model

3.3. The Chow Test

3.4. The Variables

4. Data Analysis

4.1. Results

4.2. Regression Results

4.3. Rent level drivers in Amsterdam

4.4. Comparison between Amsterdam &Rotterdam

4.5. Conclusions

4.6. Review

1.

Introduction

1.1. Private Investment in the Dutch Rental Housing Market

Over the last decade, there has been a growing investment rate in the Dutch rental housing market. The market offers valuable opportunities for private investors. As of 2014, there has been an unprecedented interest in the Dutch housing market from national and international investors alike. According to a report published by Capital Value—an advisory firm in the field of real estate— there were more than 200 international investors ready to invest in the residential housing market in 2014 (Capital Value, 2014). The same report indicated that local investors were to invest €2 billion in rented housing (twice the amount invested by international investors). The report indicates that the rental housing market in Holland started to witness a steady recovery following the housing market crisis of 2008. This recovery was marked by private investors making their entrance for the first time into the Dutch rented housing market. This has had significant implications for the private investors and the Dutch Housing associations alike.

The housing market is easily affected by socio-economic changes, such as demographic changes, income development, consumer behavior, and price fluctuation. The Dutch Housing market was badly hit by the 2008 crisis. Prior to the crisis of 2008, the presence of private investors in the housing market was insignificant. More than 85 % of the market was under the control of the Dutch Housing associations (source). During the crisis, the returns from the housing market dropped to its lowest levels and the housing association started selling a significant part of their residential blocks, both regulated and non-regulated (source). According to (same source), the Dutch rental market makes up 40 % of the total housing stock. 50 % of the rental market is now dominated by private investors. Apart from the 2008 crisis, the participation of the private sector in the rental market has been facilitated also by the tendency of the government to encourage the non-regulated housing sector.

The increasing interest in the Dutch rental housing is the most remarkable shift in the housing market in the last decade (source). This increasing interest can be ascribed to a number of socio-economic factors (source). These factors include “improved market conditions, bottomed-out house prices, attractive risk-return ratio, stable income returns and an increasing shortage on the residential real estate market” (same source). Commercial investors are turning their attention to rental apartment blocks mainly because they have low management costs and vacancy risks. In particular, private investors tend to invest in new urban areas because in most these dwellings are either non-regulated or are likely to be deregulated later (source). This is mainly because non-regulated rental housing is more lucrative. Due to the governmental control in the regulated sector, investors have limited control over rent prices. It is in the non-regulated market that investors can enjoy the benefits of free renting market.

The regulated and the non-regulated rental housing market offer different business prospective for investors. In the regulated market, the rent level is measured by valuation points (source). Valuation points are allotted to every aspect of the dwelling, including “floor space, energy index, heating, toilet, lavatory, renovation, size of kitchen” (source). Rent price within the regulated rental market must be in accordance with the market rents. On the other hand, in the non-regulated market, private investors enjoy the benefits of free renting market. According to (source), “in the period 2016 – 2018 the boundary rent level of € 710 p/m is frozen so every year less points are needed to reach the maximum rent level of € 710 p/m” (Page number). This opens up endless opportunities for commercial investors to set the rent price. Since there is no government regulation, the valuation methods vary from one investor to another. The valuation methods may have no relation with the market demand or scarcity, nor do they reflect the market rents. Accordingly, designing an appropriate valuation method for housing properties has become a necessity. It is in this context that the scope of this paper falls. It seeks to explore the drivers of the free renting market in the Netherlands and propose a valuation model that can be used to ensure fair rent prices. The paper will draw on the developments in Amsterdam and Rotterdam to generate the model. In so doing, the paper makes a comparative approach to these two cities in order to get a comprehensive understanding of the Dutch free renting market.

1.2. Research Method

This thesis will apply a hedonic regression model to determine the appropriate valuation method in the non-regulated rental market. Through hedonic regression “the value of a home can be determined by separating the different aspects of the home – number of bedrooms, number of bathrooms, proximity to schools – and using regression analysis to determine the value of each variable” (source). Since it is theoretically difficult to compare the rent levels in two or more regions, a hedonic regression model will be useful to explore the disparate rent drivers in Amsterdam and Rotterdam. The model will analyze a number of independent variables that affect fair rental levels in Amsterdam and Rotterdam. These variables include the specific features of the house, the location variables, the listing period and the listing time. The proposed model aims at analyzing and understanding the structure and the drivers of the free renting market. Ultimately, this understanding should enlighten private investors when they analyze rent levels of residential properties in Amsterdam and Rotterdam.

The literature available suggests that rent levels are key factors in property valuation method. Commercial investors use them to determine the value of a property and its prospective investment value. As a result, hedonic regression will provide real estate investors with a valuable tool to determine the fair value of residential properties. This will be a good asset for private investors who wish to reinforce their investment policy. In other words, a hedonic regression model will help investors determine which residential properties have the highest rent levels and the highest potential returns. Moreover, the proposed model will provide the different stakeholders with the necessary understanding of the drivers of the free renting market. This will help them determine the profitability of the property and any extra services/facilities they may provide to the tenants.

1.3. Research Questions

Through the application of a hedonic regression model, this thesis seeks to answer the following research questions. However, the main research question in this thesis is:

What are the major drivers of the free renting in the non-regulated rental housing market in Amsterdam?

A review of the literature available reveals that there is a perceived segmentation in the market of the non-regulated rental housing. The thesis explores the drivers of free renting market to check whether there is a market fragmentation. However, in order to get a clear idea of the market segmentation, the drivers will be studied in a separate way for the different types of the houses. However, some drivers apply to some house types but not to others. Therefore, a number of sub-questions should be addressed. These sub-questions are:

· Do rent level drivers affect all house types in the same way in Amsterdam?

· What are the differences in rent level drivers between Amsterdam & Rotterdam?

· Do rent level drivers affect all house types in the same way in Amsterdam and Rotterdam?

The thesis seeks to contribute to the literature on the Dutch non-regulated rental market. Given the fact that the non-regulated market in the Netherlands is relatively new, data on rent levels and house attributes is still scarce. Accordingly, a hedonic regression model is likely to provide empirical data on the Dutch non-regulated rental market.

1.4. Relevance of the Research

The increasing interest in the Dutch rental housing is the most remarkable shift in the housing market in the last decade. Following the 2008 crisis, the real estate market has been marked by the entrance of the private investors on the one hand, and by the tendency of the government to encourage the non-regulated rental market on the other. The academic interest in the Dutch rental market is relatively new. Accordingly, literature on the subject is still scarce. It is this context that the scope of this thesis falls. The relevance of this thesis lies in the fact that it seeks to explore the drivers of the free renting market in the Netherlands and propose a valuation model that can be used to ensure fair rent prices. Its major contribution will be to provide real estate investors with a valuable tool to determine the fair value of residential properties. This will be a good asset for private investors who wish to reinforce their investment policy. In other words, a hedonic regression model will help investors determine which residential properties have the highest rent levels and the highest potential returns. Moreover, the proposed model will provide the different stakeholders with the necessary understanding of the drivers of the free renting market. This will help them determine the profitability of the property and any extra services/facilities they may provide to the tenants.

1.5. Structure of the Thesis

The thesis is made up of four inter-related chapters. The first two chapters establish the theoretical background of the research. they introduce the concept of non-regulated rental housing in the Netherlands and review the existing literature. The first chapter is a general introduction to the thesis where the research problem, the research methods and research questions are formulated. This chapter problematizes the research topic and proposes the research method. The second chapter reviews the literature available in the field of the Dutch Housing Market. This chapter contextualizes the research problem by narrowing it down to Amsterdam and Rotterdam. The importance of this chapter lies in the way it establishes the theoretical framework for the next chapters by reviewing the previous studies. chapters 3 & 4 of the thesis are practical. Chapter 3 details the research methodology, while chapter fours presents the results of the hedonic regression model and discusses the findings.

2. Literature Review

2.1. The Dutch Housing Market

The governmental regulation of the housing market seems to be a distinctive feature. Despite the government’s encouragement of the non-regulated housing sector in the last years, the market is not completely free (source). Subdivision and a strict spatial planning policy have helped the government to maintain its control on the market. This regulation has caused home ownership to be low in the Netherlands (source). According to the current urban planning policy in the country, house-building is only possible in the suburbs (source). All these reasons contribute to keep home ownership at a rather low level despite some progress (source).

The government’s control of the housing sector extends to the rental market as well. It has followed a rigorous policy of providing social housing to people with low-incomes and of keeping a firm grasp of rental market (source). The Housing Act of 1901 has set the tone for the government’s provision of social housing and the continual improvement of the housing conditions of the people. In pursuance of this, the government pays housing allowances to people of low-income which can go up to €699/ month. This is the threshold between regulated and non-regulated rental sectors. However, the determination of the maximum rent is not a random matter. The Netherlands uses a points system known as woningwaarderingsstelsel (Property Valuation System). It assigns points to a property based on the characteristics of the house, the location and its type (source). However, the non-regulated rental market is still small. The low participation of private investors in the rental market is due not only to the evaluation system but also the restrictions on home ownership imposed by the government (source). The early private participation in the housing sector go back to the year 2012 (source). This coincides with the economic recovery after the 2008 crisis, but also with the government’s continuing encouragement of the non-regulated rental market.

It is also important to note that the government’s regulation of the housing market can affect the value of the property. In other words, one might ask here: does the point evaluation system really reflect the market conditions? The literature available suggests that there is a discrepancy between the rent levels in the regulated market and those in the non-regulated market. The Dutch points system is meant to determine the rent level for social housing, but also to serve as a guide for the free market sector. However, to be legible for social housing, applicants should have an income of no more than 34.000 Euro per year (source). In practice, this means long waiting time that is between 3 and 10 years (source). This also means that, while on the waiting list, many people have to rent in the free market and end up paying more than €699/ month. Accordingly, it can be argued that the rent level for social housing does not reflect the market conditions. According to (source), the average rent level in Amsterdam is estimated at €1900.

Moreover, there is a perceived gap in the value of the property (source). In practice, a value gap means that the price of houses is very high but the rent level is very low. In the Dutch context, the value gap is caused by the government’s social housing, the regulation of the rent and the housing allowance program (source). In its attempt to increase homeownership, the Dutch government sponsors those houses that are occupied by the owner themselves (source). This can be in the form of subsidies or through deducting mortgage rate. The value gap in the housing continues in the wake of the 2008 financial crisis. The crisis has caused the price of houses to decline by 20% and the rent level to soar by 5 %. Because of this value gap, the rent level in the Netherlands does not reflect the market conditions.

The last 5 years have witnessed a shift in the Dutch housing market. The shift consists of the increasing presence of private investors in the market. This coincides with the efforts of the government to encourage private investment. According to (source), the government “the government gradually limits interest tax deductibility for owner-occupiers, raises rents for high income households in social housing and stimulates additional non-regulated rental housing construction and the transformation of vacant office space into non-regulated rental housing (Page number). However, the presence of private investors is still insignificant compared to other European countries. In 2016, it was estimated that there were around 7.6 million houses in Holland, 40% of which is rented (source). The same study revealed that social housing made up 39 % of the total housing market while the non-regulated sector accounted only for 3 % (source). When compared to Europe, the Netherlands has the smallest free housing market (in Germany it represents 62 % of the total housing sector) (source).

2.2. The Housing Sector in Amsterdam

Of all the Dutch cities, Amsterdam witnesses a rapid demographic growth. The city is usually hailed as the premier destination for expats and tourists. According to (source), around 50 % of the population in Amsterdam have at least one foreign parent, which makes it one of the most cosmopolitan cities in Europe. This has significant consequences on the housing sector. Over the last two years, the city has seen a sharp housing shortage. The demographic changes in the city are not related only to the number of new settlers. Changes in the type of households contributes to this housing shortage. The city is witnessing an increase in the number of single households. (source). Moreover, given the percentage of expats in Amsterdam, the rental market has gone up significantly. Today, the rental market in Amsterdam is far above the national level (source). The rental market in Amsterdam represented more than 70 % of the total housing sector and around 45 % of it is non-regulated (source).

On the whole, the housing market in Amsterdam is divided between owner occupied houses, social housing and private rent houses. Owner-occupied homes represent a small percentage of the housing sector. According to (source), there are 480.000 households in Amsterdam by 2106. The following graph represents the distribution of households in Amsterdam.

Figure 1: Amsterdam Housing Market

2.3. The Housing Sector in Rotterdam

A review of the literature available on the Rotterdam housing sector reveals that the rental market accounts for nearly 70% of the overall housing market. The situation is very similar to Amsterdam. The similarity can be seen also in the percentage of non-regulated market: 18 % in Rotterdam (source) and 25 % in Amsterdam. However, what distinguishes the Rotterdam market from the rest of Holland is the availability of a good portion of affordable housing built in the wake of WWII and up to 1995 (source). with over 310,000 houses built in this era, affordable housing represents 54 % of the housing stock, compared to 40 % in Amsterdam(source). One direct result of affordable is that it lowers the price of housing. According to (source), “The average house price in Rotterdam is still notably lower than the Dutch average of €221,600, which is due to a high percentage of affordable housing in the residential stock” (page number). The non-regulated market represents 47% of the total housing market. The owner-occupied houses account for 35 % of the market. The following graph represents the distribution of households in Rotterdam.

Figure 2:

Rotterdam Housing Market

According to (source), the average rental price per square meter was €13.3 in 2015 in Rotterdam compared to €19 in Amsterdam. The average price includes all types of housing, villas, apartments, studios and family dwellings. Although Rotterdam witnessed a 9,4 % increase in rent price in 2015 compared to 2013, it still has the lowest rent price per square meter of all the big Randstad cities (source). The average rental price in 2015 was €19 in Amsterdam, €15 in Utrecht, and €13.7 in The Hague (source). It is also important to note, here, that Rotterdam offers one of the best real value money as it features a good number of new and renovated dwellings. However, the rental price inside Rotterdam varies depending on the neighborhood. for example, “At the Kop van Zuid for instance, rents per sq. m range from €11.5 to €17.0 per month for apartments” (source). In conclusion, despite some distinctive differences, the housing markets in Amsterdam and Rotterdam are similar.

2.4. Previous Studies

There has been substantial research on the drivers of the residential housing market. On the whole, these drivers can be channeled in two directions, namely demand and supply. The first direction includes the economic and the demographic factors, while the second direction is made up of such factors as construction and real estate stock (source). These drivers are interconnected and they affect each other in the short and the long run. For the sake of consistency, this part of the thesis reviews the literature available on the drivers of the free rental market based on the house attributes. However, it would methodologically appropriate to give a summary of the different drivers of the residential market. The following graph sums up these drivers in a way that captures their interconnectedness. The figure is adopted from Patrizia (2012).

Figure 3: Drivers of the Residential Housing Market. Source: (Patrizia, 2012)

Amsterdam Housing Market

Owner-Occupied Houses Privately-Rented Houses Social Housing 0.30199999999999999 0.25 0.44800000000000001

Rotterdam Housing Market
Amsterdam Housing Market

Owner-Occupied Houses Non-Regulated Rentals egulated Rentals 0.35 0.18 0.47