1 Introduction

Residential dominant developers are more likely to use margin on development cost (MDC) required to have a higher minimum internal rate of return (IRR) percentage; investor developers are more likely to use the payback period as a hurdle rate, and specific hurdle rates as a part of a go/no-go decision; trader developers adopt a higher percentage of IRR and deviate further from accepted financial theory in hurdle rate selection; and national property development organisations in multiple geographic regions use qualitative frameworks more as a decision-making process and use MDC less as a hurdle rate [1]. On the other hand, the high level of differentiation of properties and the market effects generated by this contingency in terms of anomalies and stickiness complicate the forecasting possibilities and make the data sample construction and the use of multi-parametric procedures increasingly delicate and problematic [2].

The Yadavalli and Landers [3] study examines TIF impact on assessed property value growth in Indiana using a two-stage propensity score matching method. Results suggest TIF adoption is linked to a 0.01% higher growth in assessed value and a 0.02% increase in property values for TIF properties. A proposed alternative is to, Fractional property ownership involves less than 100 percent interest, posing valuation, risk, and liquidity issues. REITs, FinTech platforms, crowdfunding enable fractional investment [4]. Rehm and Yang use rental income as a proxy for housing speculation and conclude that the vast majority of residential transactions in Auckland has been speculative to some extent [5].

Housing’s utility attributes unveil through prices of distinct products and their associated characteristics. Attributes include structural, neighborhood, environmental traits, and accessibility [7]. Best practices inform Czech Republic’s expert appraisals with mentioned factors, yet their significance remains unproven. Appraisal is both science and art [8].

Nakajima and Telyukova [9] empirically analyzed the demand-willingness of the elderly in the USA to participate in housing reverse mortgages (HRM); this study was based primarily on factors such as housing property protection, life expectancy extension and increased pension expenditure. Davidoff et al. [10] believed that information asymmetry affects the elderly’s interest in HRM and that adequate value disclosure can enhance older people’s understanding of relevant information, thereby increasing their willingness to participate in HRM. On this basis, Shu and Ming [11] conducted a comprehensive analysis of certain factors – including the individual features of the elderly, the complexity of contract clauses and the present economic situation – and constructed an economic model of the HRM in terms of the participation of the elderly in the USA.

Related research has been found to the current one, which is good; they address similar topics but the main objectives of these articles or investigations are totally different. There is a lot of similarity in works such as, “Factors explaining land value. Hermosillo, Sonora, Mexico case” by Jesús Quintana [12]. A study by the Autonomous University of Sinaloa (UAS) found that residential appreciation in Hermosillo has significantly increased in recent years, indicating that acquiring a home is an attractive investment in the city. However, the lack of access to financing is a significant barrier to acquiring a home in Hermosillo, especially for low-income individuals, according to an article by Pérez-Maldonado published in 2021 [13].

The city's urban development plan is another very important factor to consider in property appreciation, as it allows us to predict how long it will take to obtain the return on investment. All things considered, assuming we already know which property (home) we want to acquire, we need to try to predict if the property is a possible candidate for appreciation, and since we know that appreciation depends on external factors, it cannot be predicted exactly, but references of properties with similar characteristics in similar locations can be obtained to determine if the acquisition of such property is economically viable. In this research work, the appreciation of the 182 homes located in the Firenze Residencial and Alta Firenze Residencial subdivisions located north of the city of Hermosillo, Sonora, were calculated. The homes were acquired be-tween 2013 and 2021. Considering that the acquisition was through bank financing and the financial cost of those financial products was calculated, as well as the financial cost of inflation.

The residential housing market in Hermosillo, Sonora, is a growing industry with a wide range of investment opportunities. Property appreciation in Hermosillo is an important indicator for investors and homeowners. Appreciation refers to the increase in the value of a property over time. There are several factors that influence the appreciation of a property, such as location, construction quality, and market conditions. Acquiring properties through bank financing is a popular option in Hermosillo, which allows buyers to purchase a property without having to pay the full cost upfront. However, it is important for buyers to understand the terms and conditions of the loan, interest rates, and payment terms before making a purchasing decision.

2 Case study

One way to intervene in the city is through urban renewal, a term coined in 1950 by American economist Miles Calean. It refers to the renovation of buildings, facilities, and city infrastructure, necessary due to aging and deterioration, or to adapt to new uses and activities. Nowadays, urban renewal takes place in the develo** city center or its vicinity, as these areas are where the most aged and socially/economically outdated neighborhoods are located [14].

As for urban regeneration, it's known as the process of public intervention that integrates aspects of the environment, physical, social, urban, and economic conditions. It proposes alternatives to improve the population's quality of life and the conditions of buildings, urbanization, and/or population [15].

On another note, there’s the definition of green infrastructure, which refers to constructions that use living and natural systems to provide environmental and comfort services. These include containing, cleaning, and filtering water, providing shade, reducing temperatures on sidewalks, streets, and buildings, as well as traffic calming. Green infrastructure is increasingly used in communities to manage rainfall more sustainably. Semi-arid and arid areas like the Sonoran Desert face long periods of drought interspersed with intense rains that can overwhelm existing stormwater drainage systems [16].

Blue infrastructure refers to planned infrastructure for proper water management and is essential for the integrated improvement of territorial processes. This importance is not only due to issues related to water resources such as supply and treatment, aquifer recharge, or flood control, but also due to the psychological and emotional effects it generates in citizens [17].

The research is located in the Mexican Republic, in the state of Sonora, specifically in the municipality of Hermosillo (See Fig. 1).

Fig. 1
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Location in the Mexican Republic and in the state of Sonora

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The site’s location is in the city of Hermosillo, with coordinates of 29° 05' North latitude, – 110° 57' West longitude. It is situated at an elevation of 210 m above sea level (See Fig. 2).

Fig. 2
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Location of the study area

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3 Data and method

3.1 Data used

The data for this study was mainly sourced from three outlets. These include the company Promotora de Hogares S.A de C.V., the National Consumer Price Index (INPC) published by the National Institute of Statistics and Geography (INEGI) in the Economic Information Bank (BIE), and the publication “Basic Indicators of Housing Credits” by the Bank of Mexico.

Any data collection method must meet three essential requirements: reliability, validity, and objectivity. It is noteworthy that all three sources of quantitative data for this study meet these three requirements.

3.2 Methodology

The conceptualization of the methodology, as well as the three steps to achieve the objectives of this research, are presented below.

3.2.1 Definition of the research scope: exploratory and descriptive

Upon examining the detailed scope of this research, we can establish the conceptual and methodological boundaries. The research possesses an exploratory scope for the following reasons:

It investigates a scarcely studied issue.

It lays the groundwork for future research in other areas of the city.

Literature review revealed only loosely related ideas concerning current viability in property acquisition through mortgage credits, lacking clear insights into Hermosillo, Sonora's high-yield zones. Reading this research will acquaint you with these relatively unfamiliar phenomena. Rather than quantitatively and impartially analyzing these phenomena, people often rely on their "common sense" when acquiring property through mortgage credits. Therefore, familiarizing and delving deeper into the topic are of great value.

Exploratory studies rarely stand as an end in themselves. They generally identify trends or set the “tone” for more rigorous subsequent investigations [18]. This research opens the possibility for a more in-depth study of the topic, not only analyzing more zones in the city of Hermosillo, but also beginning to correlate the similarities between homes and areas. Determining the variables that contribute to appreciation or lack thereof would thus lay the foundation for a correlational study, potentially serving as a continuation of the current investigation.

Furthermore, the research also holds a descriptive scope due to:

The definition of variables.

Describing various phenomena, situations, and/or events. In other words, detailing their nature and behavior.

Our intention is to measure and gather information on the variables and thereby describe phenomena or events – essentially, outlining their manifestations. The Total Annual Cost (TAC) of financing was measured and data was collected, including interests, insurance costs, VAT, and commissions. All payments made for the requested credit were converted to their present-day equivalents considering the inflation rate provided by National Institute of Statistics, Geography, and Informatics (INEGI). By subtracting these equivalent payments from the property's current appraised value since its acquisition, we can determine whether appreciation occurred, addressing the question of whether there was indeed an increase in value.

3.2.2 Research design and sample selection

The strategy is conceived to obtain the desired information. The present research does not deliberately manipulate variables; instead, we observe phenomena that have already occurred and analyze them to obtain results and conclusions. Given the above, we classify this research as a non-experimental quantitative research design, employing a cross-sectional design.

Promotora de Hogares, one of the companies with extensive experience, quality, and creativity applied in construction and one of the most recognized housing developers in Hermosillo, Sonora, has built numerous residential complexes in the city, including Table 1:

Table 1 Housing developments developed by Promotora de Hogares S.A de C.V
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The company has provided significant and confidential information to advance and conclude this research. Promotora de Hogares S.A de C.V. has contributed with complete information from 182 homes located in Alta Firenze Residencial and Firenze Residencial. Six prototypes were used for this research, as seen in Table 2.

Table 2 Housing developments developed by Promotora de Hogares S.A de C.V
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The aforementioned company has made an exceptional contribution by sharing the following information:

  • • Prototype of models

  • • Quantity of prototypes sold

  • • Exact date of deed for each residence

  • • Technical specifications of each model

  • • Value to be received for each residence

  • Additionally, they provided other types of information that were not used for the research, such as:

  • • Block and lot number of each residence

  • • Plotting and planting

  • • Architectural blueprints for each prototype

  • • Completion date of construction (Very similar to the deed date)

All residences of each model are sold at the same price, regardless of the customer acquiring the said model or the type of financing or payment method employed by the buyer. House prices are updated as an appraisal value is applied periodically. For instance, the prices in February 2015 differ from those in April 2015. Promotora de Hogares adjusts prices every month based on supply–demand and inflation rates recorded at the end of each month. Consequently, the sample selection method is “non-probabilistic.”

3.2.3 Data collection “Basic Indicators of Housing Credits”

In Tables 3, 4, 5, 6, 7, and 8, some of the data extracted from the “Basic Indicators of Housing Credits” is presented. Various credit purposes exist, including acquisition, debt payment, construction, liquidity, among others. The extracted data displays the number of credits granted specifically for home acquisition, excluding credits in partnership with the National Housing Fund Institute for Workers (Infonavit)/Fondo de la Vivienda del Instituto de Seguridad y Servicios Sociales de los Trabajadores del Estado (Fovissste), as well as credits granted to employees and former employees of financial institutions, restructured and overdue credits, among others. Credits co-financed with National Housing Organizations (ONAVIS) are included. These credits encompass the dates shown in the tables, and in addition to the number of credits, the credit granted in millions of pesos is shown, along with the average credit term in years, and finally, the average weighted interest rate by balance in percentage.

Table 3 Home acquisition credits in force as of December 2015 by capacity and segment
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Table 4 Housing acquisition loans in force as of October 2016 by loan-to-value ratio and segment
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Table 5 Housing acquisition loans in force as of October 2016 by loan-to-value ratio and segment
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Table 6 Housing acquisition loans in force as of October 2018 by loan-to-value ratio and segment
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Table 7 Housing acquisition loans in force as of October 2019 by loan-to-value ratio and segment
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Table 8 Housing acquisition loans in force as of October 2020 by loan-to-value ratio and segment
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In Figs. 3, 4, 5, 6, 7, and 8, the distribution of credit balances for home acquisition granted by commercial banks is depicted for the dates encompassed by each figure. It is evident which were the minimum, average, and maximum interest rates granted to beneficiaries on those dates.

Fig. 3
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Source: Basic Housing Credit Indicators, Data as of December 2015

Distribution of the balance of housing acquisition loans granted by commercial banks as of December 2015.

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Fig. 4
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Source: Basic Housing Credit Indicators, Data as of October 2016

Distribution of the balance of housing acquisition loans granted by commercial banks as of October 2016.

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Fig. 5
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Source: Basic Housing Credit Indicators, Data as of October 2017

Distribution of the balance of housing acquisition loans granted by commercial banks as of October 2017.

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Fig. 6
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Source: Basic Housing Credit Indicators, Data as of October 2018

Distribution of the balance of housing acquisition loans granted by commercial banks as of October 2018.

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Fig. 7
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Source: Basic Housing Credit Indicators, Data as of October 2019

Distribution of the balance of housing acquisition loans granted by commercial banks as of October 2019.

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Fig. 8
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Source: Basic Housing Credit Indicators, Data as of October 2020

Distribution of the balance of housing acquisition loans granted by commercial banks as of October 2020.

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4 Results

4.1 Analysis of quantitative data and validation of data (study finances)

A simulator created in Microsoft Excel was used to analyze the quantitative data and validate the data (study financing). In the first phase of the simulator, the general data of the property under study were added as shown in Table 9. The prop-erty value and operating price refer to the price at which the transaction was made on a certain date. That information was extracted from the databases. The down payment requested by the bank in most cases is a minimum of 10%, so in this study it was considered that all properties were acquired with financing of 90% of the operating price. It should be clarified that there are other people who pay more than 10% down payment, but almost no one pays less. If a person pays more than 10% down payment when acquiring a property, it will be reflected in a lower monthly payment and less interest. No-tarial fees depend on the municipality and fees charged by the notary. On average, notarial fees in Hermosillo, Sonora are considered to be around 6% of the operating price. Therefore, the credit requested by the client will be 90% of the value of the property.

Table 9 Table containing general data of the house in the simulator
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Once the interest rate for the date of acquisition of the study property is obtained, the Total Annual Cost (TAC) is calculated. The TAC is the total cost of the credit and is also measured in percentage. It includes the total cost that the client pays for interest, damage, life and unemployment insurance, as well as commissions for opening, deferred payments, VAT, etc. In short, it includes absolutely all the expenses involved in contracting the credit. On average, we see that the interest rate must be multiplied by 1.19 to obtain a TAC that is very close to the real one. The results of the calculation are shown in Table 10.

Table 10 Percentage difference between the Annual Total Cost and the interest rates
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Table 10 also shows how a total of 9 simulators were used to obtain the interest rate offered by these institutions on the men-tioned dates, as well as the TAC they were charging. This way, we can make a comparison of the cost of their commissions, insur-ance, and other things. An average factor of 1.19 is obtained, meaning that the interest rates are multiplied by 1.19 to obtain the actual cost of the credits.

Continuing with the data in Table 9, we proceed to obtain the months elapsed from the date of acquisition of the property to the current date, the current value of the property, the rent value of the property, which always conservatively equates to $6,000 per million that the house is worth, and finally the current balance of the property. This refers to the remaining debt of the loan as of the current date assuming that a credit was contracted with that interest rate for a term of 240 months. The amortization table is then created.

To proceed with the creation of the amortization table, we start by calculating the monthly payment and rent as shown in Table 11. We first have a CAT of 12.95% which is used as the interest rate in the formula for this calculation. The effec-tive rate (Tef) is equal to 1.020%, which means that a monthly interest rate of 1.020% is equivalent to an annual interest rate of 12.95%. By substituting the data in the table, we obtain a monthly payment of $16,496.56, which allows us to move forward with the amortization table.

Table 11 Section of the simulator for calculating the monthly payment and rent for property 001
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In Table 11, the monthly payment and the percentage increase in the value of the property are calculated. Once the percentage increase in the property value is obtained, it is possible to determine the annual adjustment that the rent will have.

The regular amortization table is used, which includes the monthly payment, interest and insurance costs, amorti-zation, and remaining balance, as shown in Table 12.

Table 12 Regular amortization table and the financial engineering table of the simulator
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On the other side, the calculations made with Financial Engineering are displayed. The column for monthly infla-tion refers to the monthly inflation that occurred in Mexico according to the data obtained from the Consumer Price Index issued by INEGI.

The column for the monthly factor equivalent to the present refers to the number by which an x amount of money must be multiplied to obtain its equivalent at present value. For example, $1.00 pesos in December 2013 is equivalent to $1.49 pesos in February 2023. Once this factor is obtained, the calculation of the monthly payment equivalent to the present and the calculation of the rent equivalent to the present are performed.

To calculate the column of the property rent, it was assumed that the house was rented every month of the year. Rental contracts are usually for 12 months, so the price remains constant during the first 12 months of rent, and then it increases based on the increase in the property value.

To calculate the property value increase, a simple equation was used and solved. Since the initial and final value of the property and the time period that has elapsed are known, the percentage increase in value month by month and year by year can be obtained. Once the percentage increase per month is obtained, it is possible to determine the rental price for each year.

Table 13 shows the simulator results. Using the present value equivalent factor obtained by the financial engineer-ing equations, it is possible to calculate the equivalent of the down payment payment, the notarial expenses equivalent, and the equivalent of all the monthly payments at present value. The sum of all the monthly payments paid and converted to their present value equivalent is $2,290,527.94. Now it is possible to add those three concepts and obtain the total ex-penditure of the homeowner. There was a total disbursement of $2,683,578.27.

Table 13 Section showing the results in the simulator
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The same is done when calculating rental income and the difference between the remaining balance of the proper-ty and the sale price is obtained to determine the owner's profit when selling the property. We can see that a total income of $4,243,688.09 was obtained.

The difference between the total expense and income is actually the profit obtained from this operation, which is a total of $1,560,109.82. In this example, the house was acquired in December 2013 for the amount of $1,640,000, which considering the effects of inflation is equivalent to acquiring a property worth $2,456,688.09. The property currently has a price of $3,500,000, so it can be concluded in this example that the property’s appreciation was $1,043,435.45.

4.2 Experimental results and analysis

After establishing the procedure for calculating the capital gain and profit assuming the house is rented out for $6,000 pesos per million, the same calculation is performed using the minimum interest rate, average interest rate, and maximum interest rate of the 182 houses located in Alta Firenze Residencial and Firenze Residencial.

For the purpose of visualizing the results in a simpler way, graphs were made with the previously obtained results. First, we visualized the behavior of interest rates for the granting of mortgage financing. The red line shows the behavior of the maximum interest rates granted to beneficiaries on those dates. The gray line indicates the average interest rates granted to beneficiaries, and the blue line shows the minimum interest rate granted to beneficiaries. In the years between 2013 and 2015, there were generally higher interest rates. In 2016, there was a reduction in interest rates, making it a good year to acquire real estate through bank financing. Additionally, as mentioned in chapter 3 under considerations, the interest rates for 2013 and 2014 include SOFOLES, which had higher interest rates and affect the behavior of the graph in Fig. 9. SO-FOLES refer to credit-granting institutions for workers such as the National Housing Fund for Workers (INFONAVIT) and the Housing Fund of the Institute of Security and Social Services for State Workers (FOVISSSTE).

Fig. 9
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Minimum, average, and maximum interest rates for the granting of mortgage loans. Self-made

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4.3 Average profit with maximum, average, and minimum interest rates; renting the property

Below are the results of the profit obtained by simulating that the properties were acquired with the maximum interest rate during the acquisition period, the minimum interest rate during the acquisition period, and the average interest rate during the acquisition period of the property.

It can be observed that the trend in all the graphs is similar. The study was conducted on a total of 6 housing proto-types with dates from 2013 to 2021, all acquired in the locations of Alta Firenze Residencial and Firenze Residencial. Some prototypes were discontinued, so information was not obtained for them in some years, or some of them began construction from 2016, as can be seen in the tables in the images just below the graphs.

Figure 10 shows the profit in pesos for each housing prototype, and it can be clearly seen that the profit tends to be higher as more time passes since the date of acquisition. Figure 10 is shown in regressive dates, starting with the profit that exists recently and each time with houses that were acquired earlier.

Fig. 10
figure 10

Profit in pesos (MX $) from the capital gain and rent of the properties considering a maximum interest rate for their acquisition. Self-made

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4.4 Average profit with the average interest rate; without renting the property.

Most people who acquire a property do so in order to use it as their primary residence. Therefore, a simulation was con-ducted with the 182 homes assuming they were purchased at the average interest rate and assuming there was never any rental income. Table 14 shows the utility obtained by the homeowner after selling the house, assuming that no prepayments were made, the property was never rented, the interest rate granted was the average, no credit restructuring was done, and the loan term is 20 years.

Table 14 Results in Mexican pesos (MXN) of the utility obtained from acquiring the property without renting the property
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In Table 14, it can be observed that in all prototypes, there was no utility in the first 5 years after the property was ac-quired, meaning that the loan interests exceeded the property appreciation and monthly payments. From the 6th year after acquiring the property, it can be seen that the property appreciation combined with the monthly payments exceeded the loan interests. In 2016, the property appreciation paid the loan interests in Broselli, Casella A, and Fiorentina prototypes. As shown in the interest rate graph, it could be deduced that 2016 was a good year to acquire a property through bank financ-ing because the rates had been low, and the table leads to the same conclusion.

Residential property appreciation is the increase in a property’s value over time due to different factors. It is a term used to describe the increase in the value of a real estate property over time. According to García (2016), this phenomenon is the result of several factors, such as location, size, construction quality, supply and demand, among others.

As expected, the same property appreciation "pays" for the mortgage interest, and Fig. 11 shows the percentage that the property appreciation paid for the generated mortgage interests. It can be seen that in 2016, which was a year with “low” interest rates, it even paid up to 82% of the interests for the Broselli prototype.

Fig. 11
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Interests amortized by the property appreciation expressed as a percentage (%). Own elaboration

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5 Conclusion

As previously mentioned, the appreciation of a residential property is the increase in its value over time, influenced by various factors such as location, supply and demand, material costs, climate, city, cultural trends, among others. This increase in property value can benefit anyone, regardless of their educational level, profession, or business venture.

Although many people lack the capital to purchase a property outright, accessing bank financing is now more viable, being more accessible and easier to obtain. Despite the belief that bank loans are expensive or risky, the research findings demonstrate that the property appreciation “covers” the interest generated by the financing.

Both residential developments, Firenze Residencial and Alta Firenze Residencial, exhibited an annual appreciation of up to 5.7%, and both are located in the northern part of the city of Hermosillo, with easy access to Boulevard Morelos and proximity to Cerro del Bachoco. This could be directly related to Quintana's assertion that higher rental values are observed in the northern Morelos area, particularly towards Cerro del Bachoco, confirming the hypothesis 1 (Property appreciation in Hermosillo, Sonora is directly related to its location) may be correct.

After analyzing 182 properties, it was found that the tendency to gain profit increases over time after the property acquisition. By renting a property acquired through a bank loan at $6,000 pesos per month per million, a favorable profit was obtained in all 182 simulations with minimum, average, and even maximum interest rates. These results reaffirm hypothesis 3 (Purchasing properties through bank financing is a profitable endeavor). It can be concluded that making an intelligent purchase through a bank loan is a profitable endeavor even when the bank charges interest on the financing.

It was also observed that if the property owners use the property for living and do not rent it out, do not refinance the loan, and have a loan term of 20 years with an average interest rate for the properties studied, the appreciation can cover up to 82% of the interest after 6 years of property acquisition.

However, the prototype of the property is a crucial factor in terms of profitability. The Broselli and Casella A models obtained the highest appreciation among the 6 prototypes, despite having less square footage. This could be explained by the fact that, for a lower price, the same benefits of living in the same area, with the same culture, status, and services, are obtained, making models with less square footage have higher appreciation within the same development.

In conclusion, purchasing a residential property with bank financing and renting it out can be a good investment if one has the ability to pay the difference between the loan monthly payment and the rent during the initial years until the property “pays for itself.” For those who intend to use the property for living, property appreciation tends to rise and can cover a significant portion of the loan interest. The case studies showed an average of 7–5 years for the property rental income to begin covering the full mortgage payment.