Fluctuations In Housing Research Articles

EXPLORING THE NEXUS OF LOCAL AND CENTRAL BUDGET EXPENDITURES IN BULGARIA: A FUNCTION-BASED ANALYSIS OF LOCAL GOVERNMENT SPENDING

The article represents an analysis of the expenditures of local governments in Bulgaria, focussing on nine key functions, including general public services, defence, public order and safety, economic affairs, environment protection, housing and community amenities, health, education, and social protection. Using statistical data from 2017 to 2021, this study examines the distribution of expenditures at the local level and explores their interrelation with central budget allocations in 2021. The findings reveal notable trends, such as the growing emphasis on general public services, consistent funding for the education and health sectors, and fluctuations in housing, community amenities, and public order and safety expenditures. The study highlights the strategic allocation of resources to meet evolving local needs and underscores the importance of continuous evaluation and prioritisation in resource management. This research contributes to understanding the fiscal dynamics at the local level and provides valuable insights for policymakers and practitioners in optimising public finance management.

Rational housing demand bubble

We provide a unified framework with demand for housing over the life cycle and financial frictions to analyze the existence and macroeconomic effects of rational housing bubbles. We distinguish a housing price bubble, defined as the difference between the housing market price and its fundamental value, from a housing demand bubble, which corresponds to a situation where a pure speculative housing demand exists. In an overlapping generation exchange economy, we show that no housing price bubble occurs. However, a housing demand bubble may occur, generating a boom in housing prices and a drop in the interest rate, when households face a binding borrowing constraint. The multiplicity of steady states and endogenous fluctuations can occur when credit market imperfections are moderate. These fluctuations involve transitions between equilibria with and without a housing demand bubble that generate large fluctuations in housing prices consistent with observed patterns. We finally extend the basic framework to a production economy and we show that a housing demand bubble increases housing prices, which can still be characterized by large fluctuations.

The differential effects of exchange rate fluctuations on local housing price growth: evidence from Australia

ABSTRACT We investigate whether real exchange rate fluctuations contribute to the fluctuations in housing prices differently across local housing markets through the differential compositions of immigrants. We first develop a new measure of the immigrant-weighted local real exchange rate, which varies across areas and over time within Australia. Using this measure and a fixed-effect instrumental variables approach, we find that the growth in local real exchange rate positively affects housing price growth. This positive relationship is mainly driven by urban metropolitan areas.

House Price Prediction using a Machine Learning

Data mining is now widely used in the real estate market. The ability to extract data to extract relevant information from raw data makes it very useful to predict house prices, important housing features, and much more. Studies have shown that fluctuations in housing prices often affect homeowners and the housing market. A literature review was conducted to determine the appropriate characteristics and most effective models for real estate forecasting. The findings of this analysis confirmed the use of Artificial Neural Network, Support Vector Regression and XGBoost as the most efficient models compared to others. In addition, our findings also suggest that local agents and real estate agents are key to predicting real estate prices. This research will be of great benefit, especially to housing developers and researchers, to find the most important indicators for determining housing prices and to identify the best machine learning model that will be used to conduct research in this field.

A Study on the Volatility of Housing Prices based on Regional Decoupling Flow in Housing Market

Recently, housing market is experiencing the differential flow of housing prices by region. This study analyzed the volatility of the housing market using data on housing prices and transactions from January 2009 to June 2019 in Busan, Ulsan and Gyeongsangnam-do. As a result of the analysis, housing prices in Seoul were different from those in Ulsan and Gyeongsangnam-do, and there was no significant correlation with Busan. Busan, Ulsan and Gyeongsangnam-do are likely to become sympathetic in terms of fluctuations in housing prices due to their spatial proximity. This is an integrated result of regional factors such as supply and demand conditions, development situation and economic situation in the housing market and national factors such as policy regulation and activation policy. The various housing policies announced in 2009 to solve the problem of unsold housing in the local housing market have influenced the differentiation between housing prices in Seoul and Busan, Ulsan, Gyeongsangnam-do from 2009 to 2012. From 2013 to 2016, housing price volatility in Seoul, Busan and Ulsan moved in the same direction because the housing market has risen nationwide as the government s policy of easing real estate to revitalize the economy and low interest rates have combined. However, there was no correlation between housing price changes in Seoul and Busan, Ulsan, and Gyeongsangnam-do from 2017 to June 2019.

Housing and credit market shocks: Exploring the role of rule-based Basel III counter-cyclical capital requirements

This paper examines the extent to which the Basel III bank capital regulation attenuates fluctuations in housing and credit markets and fosters financial and macroeconomic stability. We use a positive housing demand shock to mimic a housing market boom and a negative financial shock for credit squeeze and economic meltdown. The results show that the rule-based Basel III counter-cyclical capital requirement effectively attenuates fluctuations in housing and credit markets and prevents bubbles. In the case of a negative financial shock, it significantly reduces the magnitude of economic meltdown. Our analysis of the transition from Basel II to Basel III suggests that it is the counter-cyclical capital buffer that effectively mitigates the pro-cyclicality of its predecessor, while the impact of the conservative buffer is marginal. In contrast to the credit-to-GDP ratio, the optimal policy analysis suggests that the regulatory authority should adjust the capital requirement to changes in credit and output when implementing the counter-cyclical buffer. Future research could extend the study by comparing the effectiveness of the rule-based Basel III with other macroprudential tools in achieving financial and macroeconomic stability.

Speculative bubbles in mass and luxury properties: an investigation of the Hong Kong residential market

Fluctuations in housing prices not only affect the financial well-being of corporations and households, but also influence the stability of economies. One of the results derived from such fluctuations is known as price bubbles. We aim to investigate whether such housing price bubbles did exist in two different residential markets of Hong Kong. The results indicate that there are bubbles in the Hong Kong housing markets before 2003, and later within the luxury market by 2008. As to what the government could do to curb speculative activities with regard to housing, the introduction of a capital gains tax on short-term transactions of flats as well as a higher housing supply are regarded as effective means.

The Macroeconomic Effects of Housing Wealth, Housing Finance, and Limited Risk-Sharing in General Equilibrium

This paper studies the role of time-varying risk premia as a channel for generating and propagating fluctuations in housing markets, aggregate quantities, and consumption and wealth heterogeneity. We study a two-sector general equilibrium model of housing and non-housing production where heterogeneous households face limited opportunities to insure against aggregate and idiosyncratic risks. The model generates large variability in the national house price-rent ratio, both because it fluctuates endogenously with the state of the economy and because it rises in response to a relaxation of credit constraints and decline in housing transaction costs (financial market liberalization). These factors, together with a rise in foreign ownership of U.S. debt calibrated to match the actual increase over the period 2000-2006, generate fluctuations in the model price-rent ratio that explain between 80 and 100 percent of the increase in the national price-rent observed in U.S. data over this period. The model also predicts a sharp decline in home prices starting in 2007, driven by the economic contraction and by a presumed reversal of the financial market liberalization. Fluctuations in the model's price-rent ratio are driven by changing risk premia, which fluctuate endogenously in response to cyclical shocks, the financial market liberalization, and its subsequent reversal. By contrast, we show that the inflow of foreign money into domestic bond markets plays a small role in driving home prices, despite its large depressing influence on interest rates. Finally, the model implies that procyclical increases in equilibrium price - rent ratios reflect rational expectations of lower future housing returns, not higher future rents.

Forecasting Capital Formation in Residential Housing

_HIs paper focuses attention upon one of the subdivisions of gross private domestic investment, the money value of new private residential construction. One of the salient characteristics of all the segments of gross private domestic investment is a tendency toward wide amplitude of fluctuation, particularly as compared with personal consumption expenditures. The construction of residential housing conforms closely to this pattern of fluctuation. As an industry it is characterized by extreme instability. It thus is a significant factor in the instability of gross private domestic investment and of the economy as a whole. Some analysts have found evidence of considerable periodicity in the data on housing construction. The record seems to indicate the existence of a short cycle, averaging about four years in length, and a major, or long, cycle of from fifteen to twenty years' duration. Between 1890 and 1950 either three or four long cycles can be discerned, depending on whether a relatively low peak in 1941 is interpreted as breaking the most recent cycle into two separate cycles. Definite peaks are found in 1909, 1926, 1941, and 1950. At this writing, 1950 is a peak, although the descent in the intervening years has not been steep. It would seem reasonable to expect, on the basis of factors specified later as being of importance in forecasting housing expenditures, that the 1950 level will not be surpassed in the near future. Although these cyclical swings and the current phase of the cycle cannot be ignored, it should be remembered that the data on past cycles show such wide dispersions around the averages that cyclical patterns cannot be followed blindly. The wide fluctuations in housing starts since 1920 are shown in Figure 1. The peaks of 1925, 1941, and 1950 are clearly evident. The number of new-housing starts increased during the early 1920's to a peak of 937,000 in 1925 and then fell off to only 93,000 in 1933. Expansion occurred in each subsequent year to 1941, after which construction was curtailed until 1945. Following the war, the industry increased its output rapidly, surpassed the 1925 level for the first time in 1949, and started a record number of 1,396,000 new units in 1950. The immediate problem of the forecaster is to evaluate the factors that have been responsible for the construction of more than 7,000,000 new nonfarm dwelling units since the end of 1945, to measure what strength remains in these forces, and thus to estimate the number of houses likely to be built in the coming months.