Price Boom Research Articles

Geopolitical risk and energy price crash risk

This paper explores the link between geopolitical risks and energy prices crash risk. Studying energy price crashes is important given the sharp fall in oil prices in 2008 and 2014. The analysis focuses on three energy markets: natural gas, oil, and coal, while it employs two measures: the negative coefficient of skewness and the down-to-up volatility, to construct proxies for crash risks. The period of examination is January 2000 to December 2023, whereas that for coal is January 2010 to December 2023. The study employs a modified version of the smooth transition autoregressive model. The results show that, within the modelling framework, coal and oil crash risks are driven by the cyclical behavior of geopolitical acts, whereas natural gas crash risks by geopolitical threats. Causality tests confirm the prediction that geopolitical tensions cause crash risks in energy markets. The results also confirm that the “Economic Activity Channel” is only valid for energy markets driven by geopolitical threats. Energy market regulators should be concerned about crash risks, given that the energy supply shows cyclical boom and bust cycles in prices and production. Crash risks could also potentially cause a fall in investments required to enhance energy efficiency.

Can corporate social performance mitigate the risk of extreme stock returns?

It is commonly believed that there exists a strong negative association between corporate social performance (CSP) and firm risk.11The authors would like to thank an anonymous reviewer for his careful reading of our manuscript and his many insightful comments and suggestions which have substantially improved the initial paper. The authors would alsolike to thank Lionel Tangy Malca and Alexandre Coureaud from HOMA Capital for fruitful and constructive discussions around the link between ESG and extremes stocks returns. To investigate the structure of this relationship, we decompose the dynamics of large U.S. company stock returns into two components: Gaussian and non-Gaussian innovations. Our findings indicate that CSP affects firm risk mainly through the non-Gaussian risk channel. In particular, it significantly reduces the magnitude of extreme returns. We find no consistent nor robust effect of CSP on the frequency of price boom and crash probability as it varies widely across industries. Last, we find no statistically significant impact of CSP on standard Gaussian volatility risk.

Impact of Oil Price Shocks on Islamic and Conventional Bank Performance: Empirical Evidence from Saudi Arabia

This paper aims to investigate and compare the effect of oil price shocks on the bank performance at the aggregate level as well as the level of conventional and Islamic banks. The Autoregressive Distributed Lag (ARDL) methodology was adopted to analyze a panel of 10 Saudi banks, including 6 conventional and 4 Islamic banks, between 2006 Q1 and 2022 Q4. The results revealed that oil price shocks have a direct impact on banking performance. A rise (fall) in oil prices led to an increase (decrease) in bank performance through the channel of price-induced bank deposits. Additionally, oil price shocks have asymmetric effects, with positive oil shocks having a greater impact on bank performance than negative shocks. The findings highlighted that conventional banks tend to benefit more from oil price shocks, especially during oil price booms, as they experience higher positive impacts. However, during oil price busts, Islamic banks were more adversely impacted by oil shocks.

House Prices and Misallocation: The Impact of the Collateral Channel on Productivity

Abstract This paper investigates the impact of local house price booms on capital misallocation within industries. Using the geographical variation provided by the Spanish housing boom (2003–7), we show that firms exposed to positive local house price shocks received more bank credit and their investment grew more when they had a higher proportion of real estate assets. This collateral channel results in an increasing dispersion of the capital-labour ratio within industries. A counterfactual calculation suggests that the capital misallocation generated by this channel can account for around 40% of the total factor productivity decline experienced by the Spanish economy during the housing boom.

Does accounting information identify bubbles for Fama? Evidence from accruals

Economists have long observed that stock price bubbles are associated with corporate overinvestment. We study the ex-ante identification of bubbles (i.e. stock price booms followed by busts) by examining industry-level investments in net operating asset (NOA) accruals and stock returns for 49 countries around the world. Consistent with overinvestment in operating assets being key to bubble formation, we document five findings: (1) NOA accruals positively forecast the eventual crash of an industry price run-up; (2) NOA accruals negatively forecast stock returns following a run-up; (3) NOA accruals are positively associated with investor sentiment; (4) higher NOA accruals forecast more disappointing earnings relative to analysts’ expectations for run-up industries; and (5) NOA accruals are sharply stronger predictors of crashes, returns and analyst forecast errors following run-ups compared to other periods. Our results provide the first evidence that accounting information identifies stock price bubbles and suggest that financial statements are important for detecting and anticipating industry- and market-level inefficiencies.

Labour supply and the cost of house price booms and busts

Fluctuations in house prices generate substantial heterogeneity in the price of purchase of similar dwellings depending on the time of purchase. These differences in the price of purchase have large effects on income-net-of-housing-costs. We document these effects using the large house price fluctuations during the recent housing boom-bust in Spain. Households can mitigate these impacts through changing labour supply. Men work more subsequent to paying higher house prices at purchase , whereas the correlation of house prices and labour supply for women is driven by selection: households where women work more, buy more expensive houses.

Commodity price volatility, institutions and economic growth: An empirical investigation

AbstractThis article investigates the role of institutional quality in transmitting effects of commodity price volatility to economic growth. To do so, we collect data on 107 primary commodity exporting countries in both developing and developed ones over the period 1976–2015. Our empirical approach is based on Solow growth model framework (Solow, R. M. (1956). The Quarterly Journal of Economics, 70(1), 65) and consists of estimating a dynamic panel model using the two‐step system GMM estimator. Our results show evidence that commodity price booms are associated with good economic performances that are unfortunately wiped out by the negative effects of price volatility in developing commodity‐dependent countries (CDCs). The main channel through which this volatility affects economic growth turns out to be through factor productivity. Finally, we have formally established that the negative effect of price volatility in CDCs is mainly due to the poor quality of institutions in these countries. These results suggest that it is important for commodity‐exporting economies, especially developing CDCs, to work on building strong economic and political institutions to guard against the risk of commodity price volatility.

Does monetary policy contribute to housing price booms? Empirical evidence from the US economy

Purpose This study aims to investigate the effect of monetary policy on housing prices for US economy. It specifically examines whether nominal or real interest rates are the key drivers behind fluctuations in housing prices in US. Design/methodology/approach Monthly data from January 1991 to July 2023 and various appropriate analytical tools such as unit root tests, Johansen’s cointegration test, vector error correction model (VECM), impulse response function and Granger causality test were applied for the data analysis. Findings The Johansen cointegration findings reveal the presence of a long-term relationship among the variables. VECM results indicate a negative correlation between nominal and real interest rates and housing prices in both the short and long terms, suggesting that a strict monetary policy can help in controlling the housing price increase in the USA. However, housing prices are more responsive to changes in nominal interest rates than to real interest rates. Additionally, the study reveals that the COVID-19 pandemic contributed to the upsurge in housing prices in the USA. Originality/value This study contributes by examining the role that nominal or real interest rates play in shaping housing prices in the USA. Moreover, given the recent significant upsurge in housing prices, this study presents a unique opportunity to investigate whether these price increases are influenced by the Federal Reserve's monetary policy decisions regarding nominal or real interest rates. Additionally, using monthly data, this study provides a deeper understanding of the fluctuations in housing prices and their connection to monetary policy tools.

Interactive influence of house prices and the repo rate on household debt in South Africa

<p><big>The recent interest rate policy decisions of the South African Reserve Bank have been criticized significantly by left-leaning political parties and civic society organisations for being anti-poor, anti-labour, and pro-capital because of their implications for household debt. Existing literature has established that interest rates and house prices are insignificant determinants of household debt dynamics in South Africa. Taking advantage of additional data for the period 2013-2022, and contrary to the previous studies, the paper maintains that house prices and the central bank policy rate play a crucial role in household debt dynamics. Applying a Markov Switching regression to quarterly data for the period 1981Q1 to 2022Q1, the paper finds that house prices and the policy rate have a significant influence on household debt dynamics. It establishes the existence of a ‘house price boom, low policy rate burden’ regime and a ‘high policy rate burden, low house price’ regime. The coexistence of the ‘house price boom’ and the ‘low policy rate’ explains the debt euphoria characterised by significant household leveraging.</big></p>

Low Interest Rates and Uncreative Destruction in the Office Market

Abstract Low interest rates were introduced in the global economy to support the weak economic growth that followed the global financial crisis. In the real estate sector, low interest rates usually lead to a boom in investment and prices. This boom, however, is not spread throughout the economy, but rather concentrated in major cities. We demonstrate this phenomenon on the example of the office market in Warsaw (Poland). While it would be beneficial for the Polish economy to develop office space in smaller cities that have an insufficient supply of modern office space, investors have focused mainly on the capital. This has not only led to an increase in the cost of building land and construction, but has also pushed some relatively new existing office buildings off the market. We call such behaviour uncreative destruction and explain why it was possible.

Monetary policy and housing market cycles

Abstract Using monthly data from 1978:M1 to 2019:M9, this paper provides empirical evidence concerning the role that monetary policy plays in the US housing market. We first show that shocks to short-run interest rates have significant impacts on house prices and that these effects are persistent. Our findings also provide evidence supporting the claim that too-low-for-too-long interest rates are responsible for the 2002–2006 US housing boom. We further investigate the different channels through which an easing monetary policy fuels the house price boom and find that faster sales and lower inventory levels in the housing market most amplify the policy effects. Lastly, we provide compelling evidence of the asymmetric effects of contractionary and expansionary monetary policies on house prices.

Reducing Costs and Creating Value in the Hotel Industry - Forced Good Practices

External business environmental challenges such as the effects of climate change and sustainable operation required hotel managers to take strategically planned action. All of this was exacerbated by the COVID-19 pandemic, which appeared in several waves from 2020, and the energy crisis resulting from the Ukrainian-Russian armed conflict. The periodic return of the pandemic has created a high level of uncertainty not only for operators but also for workers. The energy price boom that unfolded from the second half of 2021 required cost-saving solutions from market players that typically necessitate a significant investment and provide a long-term return. In the planning process, the guest experience and value-added approach became paramount, as the long payback period required forward thinking and good prediction of the future. In this article, focusing on relevant literature sources and using a constructivist grounded theory strategy, data mostly from the period between 2020 and 2022 has been collected and analysed, . The purpose of these two research questions is to answer what challenges Hungarian hotel market players face and what factors negatively impact their business during the period of 2020 and2022, as well as how hotel operators respond to the identified challenges and how these responses relate to the global best practices. In addition to studying general cost-saving practices in Hungarian hotels, the focus is on improving the guest experience and providing operators with real cost-effective operational solutions. Value creation occurs in all areas of hotel operations, including front and back-of-house work areas. Solutions such as heating system modernisation, digitalisation, organisational development and outsourcing of activities will be presented.

Regional Supply and Demand Fundamentals in the German Housing Price Boom

Abstract Over the last decade, German housing prices have increased unprecedentedly. Drawing on quality-adjusted housing price data at the district level, we show that regional fundamentals explain up to two-thirds of between-region and 77 to 87 percent of within-region variation in price growth. Price increases were driven mainly by co-movements in local demand fundamentals, notably population density and skill level. However, we further reveal systematic variation unrelated to fundamentals: overvaluation of top 7 cities, path dependency, and spatial spillovers. We infer that speculation, investor preference for liquid markets, and bounded rationality contributed substantially to the recent housing price boom in Germany.

Oil discovery, boom‐bust cycle and manufacturing slowdown: Evidence from a large industry level dataset

AbstractWe investigate the effects of giant oil discovery and boom‐bust price cycle on manufacturing using a large dataset of up to 49,481 two‐digit industry‐years across 136 countries over the period 1962 to 2012. We find that oil discovery reduces growth in manufacturing value added and wages. The effect on employment is insignificant. We also find strong association between oil discovery and manufacturing slowdown episodes. Oil price boom and bust both negatively affects manufacturing perhaps due to increasing input cost (boom) and declining demand (bust). We do not find any evidence in favour of a real exchange rate appreciation driven effect as outlined in standard Dutch Disease models. We speculate that the effect is primarily driven by an increase in the cost of locally sourced manufacturing input.

Oil price movements and agricultural production from heterogeneous sub‐sectors: Analysing the Dutch disease in an African resource‐rich economy

AbstractThe economy of a developing country like Nigeria has evolved from a strong dependence on agricultural exports in the 1960s to an unhealthy reliance on crude oil exports. This has led to a large agricultural trade deficit that requires a better understanding of the dynamic relationship between oil price booms and agricultural production. To this end, the study not only isolates the effect of oil price movements on agricultural production from heterogeneous sub‐sectors in Nigeria but also tests for Dutch disease symptoms using annual data from 1970 to 2019. Employing the auto‐regressive distributed lag (ARDL) cointegration and dynamic simulations as well as dynamic Granger causality techniques, the study shows that in the long run, oil price booms affect the food sector and the livestock sector heterogeneously. An increase in the oil price undercuts the production performance of the food sector. Also, because of the strong linkage between domestic livestock production and the global livestock market, an increase in domestic production has a weak predictive content for oil price booms. The policy implications of these findings include the sterilization of oil revenues outside the country and collaboration with foreign investors to provide much‐needed investment in the agricultural sector through various incentive schemes.

Hungary's inflationary exposures to global price movements

AbstractThis paper investigates Hungary's inflationary exposures to global price movements using a simple cost-push input-output price model and a database of inflation-to-output price elasticities (Global Inflation-to-Output Price Elasticity Database, GIOPED) developed on the basis of the OECD's Inter-Country Input-Output Tables. Inflation elasticities are decomposed into local, simple, and complex global value chain effects by applying Wang's decomposition scheme (Wang et al. 2017) to price movements and inflation. Our empirical analysis based on GIOPED elasticities shows that Hungary is highly exposed to global value chain price transmissions originating in Germany, Austria, and Russia; and in particular to changes in energy prices. The crude oil and natural gas price boom and the resulting energy crises caused a significant increase in consumer price levels in Hungary; however, this explains only a fraction of current inflation rates.

Financial shocks to banks, R&D investment, and recessions

Abstract In some classes of macroeconomic models with financial frictions, an adverse financial shock successfully explains a decrease in real activity but simultaneously induces a stock price boom. The latter theoretical result is not consistent with data from actual financial crises. This study aims to provide a theoretical explanation for both prolonged recessions and stock price declines. I develop a simple macroeconomic model featuring a banking sector, financial frictions, and R&D-based endogenous growth. Both the analytical and numerical investigations show that endogenous R&D investment and a shock hindering banks’ financial intermediary function can be key to generating both a prolonged recession and a drop in firms’ stock prices.

The empirical modelling of house prices and debt revisited: a policy-oriented perspective

The recent boom in house prices in many countries during the COVID-19 pandemic and the possibility of household financial distress are of concern among some central banks. We revisit the empirical modelling of house prices and household debt with a policy-oriented perspective using Norwegian data over the last four decades within the cointegrated VAR model. Our findings suggest, in line with previous work, a long-run mutually reinforcing relationship between these financial magnitudes, and thus the potential for the build-up of financial instabilities and spillover effects to the real economy. Applying a policy control analysis, we find that both house prices and debt are controllable magnitudes to some pre-specified target levels through the mortgage interest rate, which enables the central bank to reduce large fluctuations and bubble tendencies in the housing market. The present control analysis thus provides some useful policy implications from empirically relevant representations of two important financial factors entering the decision process of the policy maker.

Wealth and poverty in mining Africa: migration, settlement and occupational change in Tanzania during the global mineral boom, 2002–2012

ABSTRACT This article interrogates place, process and people’s quest for enhanced welfare during the 2002–2012 global mineral price boom in northwest Tanzania. Mass in-migration of miners, traders and service providers generated diversified residential settlements. Processes of occupational change and urbanization, catalyzed by acquisition of employment, land, housing and other possessions at six contrasting mining locations were compared from a geo-social perspective. Our surveyed gold and diamond mining sites represented different manifestations of the mining trajectory namely: (1) artisanal rushes, (2) mature artisanal and (3) industrial mining. The article investigates who benefitted locationally and who lost in residents’ scrambles to gain improved living standards. Survey data on 216 household heads’ occupations, educational backgrounds, consumption and investments were collected, followed by construction of a household welfare index, revealing modest welfare improvements relative to rural consumption norms for the majority of interviewed resident households. However, in line with Picketty’s theoretical insights, extreme material inequality surfaced on the welfare spectrum between the outlier affluent and poor quintile groups. Those with higher educational attainment enjoyed superior welfare and occupational status, coalescing towards middle class formation. At the opposite end, single female-headed households stood out as extremely disadvantaged, handicapped by high child dependency ratios and occupational immobility.

Effects of Conditional Oil Volatility on Exchange Rate and Stock Markets Returns

Saudi Arabia experienced extreme volatility in oil price booms during a short period due to COVID-19, which traded for 16 days. The oil price boom period has received significant attention as it is essential to a nation’s economic sector. The objective of this study was to examine how changes in oil volatility under specific conditions affect the stock market return indices and exchange rate of Saudi Arabia. The Saudi Arabia capital market was used as the case study, while the average daily exchange rate and stock market were employed as the primary variable. This study covers the period from March 21, 2014, to November 19, 2020. The wavelet methodology was used for data analysis. The study's findings revealed that oil is not a safe haven for the bond market in Saudi Arabia. Similarly, oil-primarily functions as a safe haven for a short period that last for 16 days. The findings revealed that oil price fluctuation has no impact and a safe haven effect on the various deals in the Saudi Arabian capital market. It also suggests that market participants focus on oil price trading as a significant tool for determining the volatility of stock market returns in underdeveloped countries.