Term Investment Decisions Research Articles

CAPITAL BUDGETING

The project talks about a capital budgeting and its methods including discounted cash flow, payback, and throughput analyses. The process involves analyzing a project’s cash inflows and outflows to determine whether the expected return meets a set benchmark, we are going to talk about how capital budgeting is also important for small and big companies to evaluate major projects and investments, such as new plants or equipment. In the present scenario the efficient allocation of capital resources is a most important function of project management. This function involves firm’s decision to invest its funds in long-term assets like plant, machinery land, building, equipment etc. These assets are extremely important to the firm because the organizational profits are derived from the use of its capital investment in assets which represent a long-term commitment of funds. The future development of an enterprise depends on the capital investment projects. These projects may be the replacement of existing capital assets which turns out to be less attractive to the firm or expansion of business for implementing new ideas and planning. Thus, long term investment decisions of an enterprise fall within the definition of project budgeting or capital expenditure decisions. These decisions are concerned with the acquisition of assets in which funds will be invested by an enterprise. The assets of business include long term assets and short-term assets. Long term assets will yield a return over a period of time whereas short term assets are those assets which are easily convertible into cash within one accounting period, normally a year. The long-term investment decision is known as project budgeting/capital budgeting and the short-term investment decision are identified as working capital management.

Connectedness between (un)conventional monetary policy and islamic and advanced equity markets: A returns and volatility spillover analysis

Using the spillover index, we investigated the relationship between Islamic equity markets and unconventional monetary policy(UMP) in five advanced economies. We documented that the spillovers among equity markets (“intraconnectedness”) are stronger than the spillovers among equity markets and monetary policy (“interconnectedness”), based on a static analysis of both returns and volatility. Second, the time-varying total spillover index showed that the Islamic market is a dominant net receiver of returns and volatility shocks. Furthermore, their spillover effect strengthened during the financial turmoil and UMP periods. Third, the time-varying net spillover effects implied that the US is the most dominant transmitter of return shocks, whereas the EU and UK are the dominant transmitters of volatility shocks. In addition, the US and Canada are the dominant transmitters of monetary policy shocks, whereas Japan is the main net receiver of these shocks. These results will be useful to investors, portfolio managers, and regulators in terms of investment decisions, portfolio allocation, and risk monitoring.

Stock Liquidity and State Ownership: Evidence from the Banking Industry of Selected Asian Emerging Markets

Manuscript type: Research paper Research aims: Liquidity creation is deemed important in the emerging markets banking industry. It turns out to be more challenging when subject to ownership issues, particularly state ownership. The government possesses substantial ownership in many large banks in Asian emerging markets and has a significant effect on firms’ stock liquidity through trading activity. Hence, state ownership is a key determinant of stock liquidity. This paper investigates the effect of state ownership on stock liquidity in Asian emerging markets. Design/Methodology/Approach: Using the GMM panel regression model, this study examines a sample of 209 banks in Asian emerging markets including China, India, Indonesia, Malaysia, Pakistan, Philippines, South Korea, Taiwan, and Thailand from 2009 to 2018. For the robustness test, an alternative liquidity measure is conducted. Research findings: Results show that state ownership is positively related to stock liquidity, implying that the participation of the government provides investors’ confidence and perceives these stocks as value-enhancing stocks. However, this positive effect on stock liquidity turns out to be negative when the state ownership surpassed a certain threshold. Thus, this paper finds a non-linear inverse U-shaped relationship between state ownership and stock liquidity. Further analysis also shows that large banks tend to enjoy greater liquidity compared to smaller banks. Theoretical contribution/Originality: Unlike past studies that focus on other ownership structures, this study focuses on state ownership of large banks in emerging markets. This study contributes by collectively addressing the impact of state ownership on stock liquidity, with a focus on the banking industry in the Asian emerging markets context. Practitioner/Policy implications: The findings of this study can benefit investors, policymakers, and other stakeholders to better understand the impact of state ownership on stock liquidity. There are various implications in terms of investment decisions and corporate governance policies pertaining to corporate ownership structure. Research limitation: Future studies may consider conducting sub-samples using a different threshold of state ownership. Besides, this study focuses on the banking sector and hence the results may not be generalised.

Capital Budgeting Technique Used in Nepalese Manufacturing Small and Medium Sized Enterprises

This paper examines the extent of usage of capital budgeting techniques in small and medium sized enterprises (SMEs) and factors influencing on the choice of capital budgeting techniques adopted by SMEs. A self-administered structured questionnaire survey was conducted with 48 small and medium sized manufacturing enterprises operated in Banke district and information has been gathered through questionnaires and personal interviews. The respondents were chief financial officer and concerned authorities of the firm responsible for long term investment decision. Results of the study reveal that payback period is the dominant capital budgeting technique used in SMEs. The results found that net present value was also the most prevalent capital budgeting method. Net present value as the capital budgeting technique is higher in SMEs who operate in the industry for more than 10 years. Easy to explain to top management, obsolescence due to technological developments and simplicity leading to less time and cost involved revealed the main reasons for using the payback period method. Some of the firms are using discounted cash flow methods of capital budgeting and preferring net present value over internal rate of return.

Enhancing the evaluation of Energy Investments by supplementing traditional discounted cash flow with Energy Return on Investment analysis

Energy companies, like companies more generally, routinely have to make investment decisions by comparing alternative investment projects. In the face of the uncertainty of the current energy transition, traditional economic tools, such as discounted cash flow (DCF) analysis, that depend on long term cash forecasting, offer limited, deterministic and potentially misleading insights. Additionally there are many pressures on companies to expand decision making criteria to “ESG” (Environmental, Social and Governance) considerations. But these are often qualitative with no clear standards, leaving investors often forced to make significant investments based on poorly understood, at times misleading and even self-defeating considerations. We explore the application of Biophysical Economics (BPE), an approach to economics based on the natural sciences, as an alternative to provide an additional lens that cuts through the uncertainty and political pressures to help companies navigate this uncertainty and make more robust long term investment decisions. The most immediately useful tool within BPE is the concept of Energy Return on Energy Invested (EROI). Specifically we compare an investment case for oil companies, one in oil sands vs. one in microbial-enhanced oil recovery, applying the two methodologies in parallel. Results from a traditional economic perspective weakly favor the oil sands, whereas biophysical economics strongly favors the microbial case due to is significantly lower energy requirement to produce the energy that it yields. A close examination indicates that EROI can be used effectively and practically next to DCF to provide better insights and identify cases that are fundamentally less sustainable for society.

Household investment diversification amid Covid-19 pandemic: Evidence from Chinese investors

This paper finds the degree of investor's investment diversification is found to be positively correlated with confirmed cases in the city where they live. This relationship is a result of stricter quarantine policy adopted by cities hit with more severe Covid-19 outbreak, which has led to increased time for investors to trade stocks and seek advisory. In addition, the employment of investors in these cities is often negatively affected. Therefore, they tend to hold a relatively pessimistic view on expectations of future income, and thus be more cautious and risk-averse in terms of investment decisions.

Feeling Right: Regulatory Fit Theory and Early-Stage Entrepreneurial Investment Decisions

Abstract Recent advances in entrepreneurial investment decisions research implied that early-stage investment decisions, given their extreme uncertainty and unpredictability, were results of investors’ intuition processes. In other words, investors manage the high risks of early-stage investment decisions by finding justifications of future value against risk in the invested entrepreneurial projects. Although some studies have discussed the decision-making process of mid- and late-stage venture capital, there is still a lack of discussion on the early-stage investment decision-making mechanism. In this paper, we draw on regulatory fit theory to theorize how the fit of regulatory focus between investor and entrepreneur could lead to the investor’s early-stage investment decisions in terms of investment amount and speed. Across three experimental studies, we found empirical support for our proposed model. Specifically, investors who have similar regulatory focus with the entrepreneurs are more likely to invest a larger amount of funds at a faster speed. We further found that investor’s sense of rightness mediates the relationship between regulatory fit and investment decision, and investor’s previous investment experience plays a moderating role.

Keputusan Investasi Keluarga Ditinjau dari Perilaku Herding dan Risk Tolerance serta Faktor Demografi: Studi di Kota Tasikmalaya

According to behavioral finance theory, a person's investment decisions can involve aspects or elements of behavior, so that they are influenced by irrational attitudes. This study aims to determine individual behavior in making family investment decisions in terms of herding behavior and risk tolerance as well as demographic factors in the community in the city of Tasikmalaya. Primary data was taken by distributing questionnaires with snowball sampling technique and collected as many as 247 samples. Data were analyzed using crosstabs analysis and multiple regression analysis. The results of the descriptive analysis showed that the people of the city of Tasikmalaya are more likely to choose to invest in moderate risk assets and low risk assets, with a fairly low level of herding behavior and a fairly low level of risk tolerance. The results of the crosstabs analysis showed that there was no significant difference in determining the choice of the type of family investment, between women and men in the Tasikmalaya city community. However, the results of the analysis of other demographic factors, namely marital status, income, and age, there are significant differences in determining the choice of the type of family investment. The results of the multiple regression test showed that herding behavior and risk tolerance, simultaneously, had a significant effect on family investment decisions in the community in the city of Tasikmalaya. The results also showed that partially herding behavior had no significant effect on investment decisions in the community in the city of Tasikmalaya, but risk tolerance partially had a significant effect on investment decisions in the community in the city of Tasikmalaya..

Environment and Potential Affecting Investment Decision for Accommodation Business: Case of Less Visited Area in Samut Songkhram and Phatthalung Province

Investment decisions have great importance in different sectors of various countries and these decisions are the basis on which the outcomes of the investments are based. However, there might be certain factors that might lead to the incorrect long term and short term investment decisions. In this regard, the current study has been conducted with the core motive to explore the impact casted by the environment and potential factors i.e. salience and overconfidence on the long term investment decisions for accommodation business along with the moderation of a variable i.e. financial literacy. To fulfill this objective, the researcher has collected data from the investors of accommodation businesses in Thailand. The collected data has been subjected to different statistical techniques and tools for analysis purpose and the results have been obtained. The results obtained by the analysis of the collected data indicate that salience and overconfidence have significant impact on the long term investment decision. In addition, the moderating role of financial literacy has also been found as significant in the study. The results suggest that the investors of the accommodation business must consider the aspects of salience and overconfidence before taking any long term investment decision to avoid failure of the investment decision.

Time series modelling, NARX neural network and hybrid KPCA–SVR approach to forecast the foreign exchange market in Mauritius

PurposeThis study constructs time series model, artificial neural networks (ANNs) and statistical topologies to examine the volatility and forecast foreign exchange rates. The Mauritian forex market has been utilized as a case study, and daily data for nominal spot rate (during a time period of five years spanning from 2014 to 2018) for EUR/MUR, GBP/MUR, CAD/MUR and AUD/MUR have been applied for the predictions.Design/methodology/approachAutoregressive integrated moving average (ARIMA) and generalized autoregressive conditional heteroskedasticity (GARCH) models are used as a basis for time series modelling for the analysis, along with the non-linear autoregressive network with exogenous inputs (NARX) neural network backpropagation algorithm utilizing different training functions, namely, Levenberg–Marquardt (LM), Bayesian regularization and scaled conjugate gradient (SCG) algorithms. The study also features a hybrid kernel principal component analysis (KPCA) using the support vector regression (SVR) algorithm as an additional statistical tool to conduct financial market forecasting modelling. Mean squared error (MSE) and root mean square error (RMSE) are employed as indicators for the performance of the models.FindingsThe results demonstrated that the GARCH model performed better in terms of volatility clustering and prediction compared to the ARIMA model. On the other hand, the NARX model indicated that LM and Bayesian regularization training algorithms are the most appropriate method of forecasting the different currency exchange rates as the MSE and RMSE seemed to be the lowest error compared to the other training functions. Meanwhile, the results reported that NARX and KPCA–SVR topologies outperformed the linear time series models due to the theory based on the structural risk minimization principle. Finally, the comparison between the NARX model and KPCA–SVR illustrated that the NARX model outperformed the statistical prediction model. Overall, the study deduced that the NARX topology achieves better prediction performance results compared to time series and statistical parameters.Research limitations/implicationsThe foreign exchange market is considered to be instable owing to uncertainties in the economic environment of any country and thus, accurate forecasting of foreign exchange rates is crucial for any foreign exchange activity. The study has an important economic implication as it will help researchers, investors, traders, speculators and financial analysts, users of financial news in banking and financial institutions, money changers, non-banking financial companies and stock exchange institutions in Mauritius to take investment decisions in terms of international portfolios. Moreover, currency rates instability might raise transaction costs and diminish the returns in terms of international trade. Exchange rate volatility raises the need to implement a highly organized risk management measures so as to disclose future trend and movement of the foreign currencies which could act as an essential guidance for foreign exchange participants. By this way, they will be more alert before conducting any forex transactions including hedging, asset pricing or any speculation activity, take corrective actions, thus preventing them from making any potential losses in the future and gain more profit.Originality/valueThis is one of the first studies applying artificial intelligence (AI) while making use of time series modelling, the NARX neural network backpropagation algorithm and hybrid KPCA–SVR to predict forex using multiple currencies in the foreign exchange market in Mauritius.

Use of computer tools in small and medium-sized enterprises: Statistical model for the creation of financial value in the productive sectors

This presents the use of computer tools for the evaluation of the generation of financial value of small and medium-sized enterprises in the municipality of Ocaña, department of Norte de Santander, Colombia. In this regard, since small and medium-sized enterprises are organizations that promote economic development, it became necessary, through the use of computer tools, to use a statistical model that evaluates in financial terms the value creation of the productive sectors. As a result, the research, using a descriptive and correlational methodology, established the computational tools to be used for the design of the statistical model, which will characterize the main determinants in the creation or destruction of value of the business structure by means of the variables of permanence, number of employees, and commercial activity. From the point of view of financial management, the financial structure was evaluated with the statistical model, establishing in terms of investment decisions, financing, and liquidity how these organizations are financially positioned; therefore, by means of statistical correlations, the relationship of dependence of financial management on the creation or destruction of value was determined.

The Crowdfunding Effects on Venture Capital Investments

We study how crowdfunding, as a source of public information, affects competing venture capital (VC) firms' investment decisions in terms of the timing, likelihood, and expected amount of VC investment in a startup. Our economy consists of one startup, one crowdfunding platform, and two VC firms with differing prior beliefs about the startup's probability of success. The startup first approaches both VC firms for funding, which is modeled as a second-price auction between the two firms, and then turns to the crowdfunding platform if rejected by both. After the crowdfunding, the VC firms update their assessments of the startup's success based on the information collected from the crowdfunding platform, and the startup seeks funding from them again. We find that crowdfunding and the competition between the VC firms raise the expected amount of VC investment. Moreover, crowdfunding increases the chance of a startup receiving VC funding only for those startups deemed unfavorable by both VC firms; for debatable startups about which VC firms' views diverge, crowdfunding may reduce their chance of receiving VC investment. We then examine how the relationship between crowdfunding and VC investment is shaped by the characteristics of the startup and the crowdfunding platform. For instance, when the more optimistic VC firm has a moderate expectation for the startup and the investment risk is high (resp., low), that VC firm tends to invest before the startup seeks crowdfunding if the crowdfunding information is sufficiently accurate (resp., noisy). Finally, we observe more nuanced crowdfunding effects in several model extensions, for example, if the startup is allowed to strategically decide on the timing to receive a VC investment, and if VC firms can observe private signals on the startup.

Financial Statement Analysis and Investment Decision Making in Commercial Banks: A Case of Bank of Kigali, Rwanda

This research analyzed the contribution of financial statements in investment decision making of banks in Rwanda taking the case of bank of Kigali. The study ascertained benefits of financial statements analysis; it analyzed obstacles of investment decisions faced by Bank of Kigali; and it established the correlation of investment decisions and financial statements analysis of Bank of Kigali. This study is significant to different beneficiaries, such as researcher, other researchers and National Bank of Rwanda. Both a descriptive and a correlational research design were adopted and quantitative and qualitative methods were used 0.126 managers were targeted and 96 managers were sampled and a stratified random sampling technique was utilized in bank of Kigali. Data from the field was collected using questionnaire and a documentary analysis where financial reports of the bank from 2014 to 2018 were analyzed. This research used correlation analysis and SPSS version 22.0 for analysis. The finding revealed that holding independent variables constant to a constant zero, short term investment decision would be at 0.266 for common size analysis while the most significant p-value was 0.008. The finding revealed that holding independent variables constant to a constant zero, Vertical analysis would be at 0.215 for horizontal analysis and element enhanced ratio analysis in the term investment decision limited by a factor of 0.001 correlated with the long term investment decision. It is concluded that understanding financial statement analysis provides that is very important to those who have the businesses as tools for reducing the considerable risks involved in starting and growing the business. Financial status of Bank of Kigali need to be maintained through the enhancement of good flow of deposits, savings and repayment arrangements to enable it serve its members while enhancing quality decisions for better service provision and also there is a need to invest in business, technology, product development, training and effective risk management systems that may be facilitated by bold decisions for the life of the company. It is also recommended to always mitigate risks while enhancing innovations and development.

Behavioral Biases as Predictors of Investment Decision of Individual Investors in Pakistan

Behavior Finance is a new field that combines attitudes, cognition, emotions, and feelings of cognitive psychology. This phenomenon explains why investors make rational financial decisions in the stock market. It also outlines the consequences of the interaction between investors and managers in financial and capital markets. And it offers more efficient options for investors and managers. Behavioral finance seeks to better understand and explain how behavioral, emotional, and cognitive factors affect investing in stock markets. Stock markets can positively impact economic growth by encouraging savings among individuals and providing opportunities for strong financing. Liquid stock markets can improve the distribution of capital and increase long-term growth prospects. Behavioral bias comes from behavioral finance theory, a theory that embraces finance and psychology. The idea of behavioral finance has started to gain importance since it became clear that people and markets are not rational. It is now clear that investors cannot succeed until they begin to exploit traditional finance theory's sophisticated techniques of behavioral finance. The present study seeks to explore the concept of overconfidence and self-attribution in the Lahore Stock Exchange market as a predictor of investment decisions in terms of age, gender, education level, and work experience. The results of the study are expected to be useful to develop guidelines for financial advisers, financial institutions, and investors.

A multicriteria assessment model for countries’ degree of preparedness for successful impact investing

Purpose In recent years there has been a significant acceleration in the market growth of social impact investing. Policy makers, regulatory bodies and national decision-makers should base their decision-making processes on multiple criteria. These criteria are, by nature, imprecise, ambiguous and uncertain. The purpose of this paper is to provide decision-makers with a mathematical tool which aids them in their decision-making processes identifying the degree of appropriateness of less developed countries in terms of potential success of investment in vaccination campaigns. Design/methodology/approach In this work, the authors have developed a decision-making tool within the framework of multiple criteria decision making and Fuzzy Logic, which aims to aid decision-makers for vaccinations campaigns in less developed countries. In particular, the authors have proposed a Technique for Order Preference by Similarity to Ideal Solution-based method which is able to work in fuzzy environment in order to assess and rank countries based on their fuzzy degree of appropriateness for impact investing in vaccines. Findings The impact investing market provides capital from private sources to address many pressing global challenges such as access to basic services as health. Governments have, therefore, an essential role in supporting the development of this market by improving the risk/return profile of investments through access to credit facilities, tax credits or subsidies or defining the regulation of the supply of investments, provision of technical assistance to investing private companies and co-financing. The proposed framework permits funding decision making taking into account the degree of preparedness and adequacy for impact investing in vaccines of the selected countries. Research limitations/implications Impact investing can play a key role in the reduction of immunization gap offering suitable strategies for both, governments and private investors for the achievement of United Nations Sustainable Development Goals (SDGs). However, in order to make good financial decisions managers should take into account not only health, income, education and other social criteria but also the degree of basic preparedness of the countries in order to ensure the success of the immunization campaigns which means taking into account availability of basic infrastructures, access to electricity, political stability among other criteria. Practical implications However, in order to make good financial decisions managers should take into account not only health, income, education and other social criteria but also the degree of basic preparedness of the countries in order to ensure the success of the immunization campaigns which means taking into account availability of basic infrastructures, access to electricity, political stability among other criteria. Originality/value The proposed model will allow public and private decision makers to make better investment decisions in terms of effectiveness as the provided ranking of countries candidates for the investments is more realistic and takes into account more decision dimensions.

Risk-conscious optimization model to support bioenergy investments in the Brazilian sugarcane industry

The past decades have seen a diversification of the sugarcane industry with the emergence of new technology to produce bioenergy from by-product and waste process streams. Given Brazil’s ambitious goal of reducing green-house gas emissions by over 40% below 2005 levels by 2030, it is of paramount importance to develop reliable decision-making systems in order to stimulate investment in these low-carbon technologies. This paper seeks to develop a more accurate optimization model to inform risk-conscious investment decisions for bioenergy generation capacity in sugarcane mills. The main objective is for the model to enable a better understanding of how Brazilian government policies, such as the electricity price in the regulated market, may impact these investments, by taking into account the uncertainty in sugar, ethanol and spot electricity markets and the interdependency between production and investment decisions in terms of saleable product mix. The proposed methodology combines portfolio optimization theory with superstructure process modeling and it relies on simple surrogates derived from a detailed sugarcane plant simulator to retain computational tractability and enable scenario analysis. The case study of an existing sugarcane plant is used to demonstrate the methodology and illustrate how the model can assist decision-makers. In all of the scenarios assessed, the model recommends investment in extra bioelectricity capacity via the anaerobic digestion of vinasse but advises against investment in second-generation ethanol production via the hydrolysis of surplus bagasse. Furthermore, the decision to upgrade the cogeneration system with a condensation turbine is highly sensitive to the electricity price practiced in the regulated market, capacity constraints on the sugar-ethanol mix, and the accepted level of risk. Another key insight drawn from the case study is that recent market conditions have favored a production focused on the sugar business, making it challenging for policy-makers to create attractive scenarios for biofuels. Long-term electricity contracting appears to be the main hedging strategy for de-risking other products and investments in the sugarcane business, provided it is priced adequately.

SMACS MODEL, a stochastic multihorizon approach for charging sites management, operations, design, and expansion under limited capacity conditions

Abstract The increasing demand of electric vehicles creates challenges for the electric grid both on the transmission level and distribution level. Charging sites in particular will have to face strong challenges especially in those countries where a massive penetration of electric vehicles happened in the last years and even more is expected in the forthcoming future. Such an increased forecast demand will lead to a capacity lack within the existing charging sites, therefore new investments in design and expansion have to be planned. We propose the so called SMACS MODEL that stands for Stochastic Multihorizon Approach for Charging Sites Management, Operations, Design and Expansion under Limited capacity conditions. The model is built to analyse critical decisions in terms of transformer expansion, grid reinforcements, renewable installation and storage integration, over a time horizon of 10 years, with a particular focus on the long term uncertainty in the price variations of the available resources. Long term investment decisions and short term operational decisions are addressed simultaneously in a holistic approach that includes also battery degradation issues and is able to tackle the optimal trade off between battery replacements, grid reinforcements and renewable installations throughout the chosen time horizon. Compared to traditional decision approaches the model is able to take more precise decisions due to its higher insight on the long term costs projections, the inclusion of battery degradation issues and the inclusion of grid rules and regulations limits that affect the final decisions.

Bubble on real estate: the role of altruism and fiscal policy

Abstract In this paper, we are interested in the interplay between real estate bubble, aggregate capital accumulation and taxation in an overlapping generations economy with altruistic households. We consider a three-period overlapping generations model with three key elements: altruism, portfolio choice, and financial market imperfections. Households realise different investment decisions in terms of asset at different periods of life, face a binding borrowing constraint and leave bequests to their children. We show that altruism plays a key role on the existence of a productive real estate bubble, i.e. a bubble in real estate raising physical capital stock and aggregate output. The key mechanism relies on the fact that a real estate bubble raises income of retired households. Because of higher bequests, there children are able to invest more in productive capital. Introducing fiscal policy, we show that raising real estate taxation dampens capital accumulation.

Pengambilan keputusan investasi Investor di pasar modal indonesia ditinjau dari Teori reasoned action

Penelitian ini bertujuan untuk mengkaji factor-faktor yang mempengaruhi perilaku investor ketika melakukan keputusan investasi ditinjau dari Teori Reasoned Action. Penelitian melibatkan 190 investor di pasar modal Indonesia dan analisis dilakukan dengan regresi linier berganda. Uji hipotesis dengan t-test untuk menguji pengaruh variabel independen secara parsial terhadap variabel dependen. Hasilnya menunjukkan bahwa Faktor Makro berpengaruh positif signifikan terhadap informasi teknikal. Informasi keuangan, faktor makro dan norma subyektif berpengaruh positif dan signifikan terhadap niat investor. Niat investor dan informasi keuangan berpengaruh positif signifikan terhadap keputusan investasi. Lebih jauh hasil penelitian ini menjelaskan bahwa informasi keuangan memegang kontribusi besar dalam membentuk niat investor dan keputusan investasi.

Bubble on Real Estate: The Role of Altruism and Fiscal Policy

In this paper, we are interested in the interplay between real estate bubble, aggregate capital accumulation and taxation in an overlapping generations economy with altruistic households. We consider a three-period overlapping generations model with three key elements: altruism, portfolio choice, and financial market imperfections. Households realise different investment decisions in terms of asset at different periods of life, face a binding borrowing constraint and leave bequests to their children. We show that altruism plays a key role on the existence of a productive real estate bubble, i.e. a bubble in real estate raising physical capital stock and aggregate output. The key mechanism relies on the fact that a real estate bubble raises income of retired households. Because of higher bequests, there children are able to invest more in productive capital. Introducing fiscal policy, we show that raising real estate taxation dampens capital accumulation.