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The conventional and new inflation bias theories present two distinct facets to explain the outcome of excess inflation without output gains by a discretionary central banker. First is the temptation to achieve a higher than potential output, and, second is not to let it falter. The authors explicitly account for these two distinct dimensions in empirical formulations both exogenously and endogenously. Specifically, the purpose of this paper is to investigate what monetary discretion can and cannot do in terms of dual objectives – inflation and growth – across boom and bust cycles, both directly and indirectly.

(i) Segregate the economic activity into boom and bust cycles; (ii) Explicitly account for the two dimensions of conventional and new inflation bias theories; and (iii) model and estimate the direct and indirect effects of monetary discretion across business cycles.

The results indicate considerable asymmetries in the effects of monetary discretion and distribution thereof across objectives and cycles. The direct impact of monetary discretion tends to induce significantly higher inflation in boom and bust cycles, while it exerts a positive but insignificant effect on output. The inflation effects are more pronounced in boom than bust cycles and vice versa are the output effects. The indirect effects on output via inflation are significantly pernicious, which are more pronounced in expansions than recessions.

In a nutshell, instead of benefiting, monetary discretion tends to harm in terms of both the dual policy objectives, which cautions about its well calculated and constrained use only.

Although recent public attention has focused on boom-and-bust cycles in industries and financial markets, organizational theorists have made only limited contributions to our understanding of this issue. In this chapter, I argue that a distinctive strategic insight into the mechanisms generating boom-and-bust cycles arises from a focus on entrepreneurial inertia – the lag time exhibited by organizational founders or investors entering a market niche. While popular perceptions of boom-and-bust cycles emphasize the deleterious effect of hasty entrants or overvaluation, I suggest instead that slow, methodical entries into an organizational population or market may pose far greater threats to niche stability. This proposition is explored analytically, considering the development of U.S. medical schools since the mid-18th century.

This paper estimates the sensitivities of the output of the manufacturing industries of the four Southeast countries (Indonesia, Malaysia, Philippines, Singapore) to both the country-specific and global business cycle fluctuations. The study investigates whether the business cycle exposures of these industries differ to their nature classified as producing durable or nondurable goods and also to booms and recessions.

Using annual time series data on sectoral manufacturing production indices for major manufacturing industries over the period from 1999 to 2018, this paper uses the seemingly unrelated regression (SUR)–based generalized least square estimator to estimate the exposures of each industry for each of the four countries to local and world business cycle.

The individual country analysis indicates that generally the sensitivities of the ASEAN manufacturing industries to booms and recessions are different from the pattern observed in the developed countries and Russia. We do not find evidence consistent with the commonly held view among economists and business managers that demand for durable goods flourishes in booms and falls in recessions. Also, very few industries exhibit an asymmetric reaction to booms and busts. However, the analysis of panel data reveals the expected pattern of industrial sensitivities to the local business cycle only.

The paper makes several contributions. Firstly, the model proposed in the paper estimates sensitivities of industries to both the local and global business cycle variations. Secondly, the model enables us to explicitly test the asymmetric reaction of industries to booms and busts. Thirdly, the paper is the first attempt to estimating business cycle exposures for manufacturing industries in emerging markets.

In this paper we investigate the relationship between loose monetary policy, low inflation, and easy bank credit and house price booms.

Using a panel of 11 OECD countries from 1920 to 2011 we estimate a panel VAR in order to identify loose monetary policy shocks, low inflation shocks, bank credit shocks, and house price shocks.

We show that during boom periods there is a heightened impact of all three “policy” shocks with the bank credit shock playing an important role. However, when we look at individual house price boom episodes the cause of the price boom is not so clear. The evidence suggests that the house price boom that occurred in the United States during the 1990s and 2000s was not due to easy bank credit.

Shocks from the shadow banking system are not separately identified. These are incorporated into the fourth “catch-all” shock.

Our evidence on housing price booms that expansionary monetary policy is a significant trigger buttresses the case for central banks following stable monetary policies based on well understood and credible rules.

This paper uses historical evidence to evaluate the relative importance of three main causes of house price booms. Our results bring into question the commonly held view that loose bank credit was to blame for the U.S. house price bubble of the later 1990s.

The purpose of this paper is to compare and contrast three‐factor models of boom and bust from Henry George, Knut Wicksell and Mason Gaffney.

The approach takes the form of an analysis and discussion and mathematical appendix.

It was found that gaffney modifies and incorporates features of both George and Wicksell into his own model.

The works of George, Wicksell and Gaffney are highly relevant, especially given the current economic crisis.

The paper should be useful both to historians of economic thought and contemporary economists. It brings together ideas that have been neglected in recent years, and contributes to the understanding of economic crises.

This study aims to investigate the determinants of homeowners’ planned holding periods. Real estate market is known for displaying buying and selling behavior that does not conform to traditional economic theories such as rational expectation or expected utility. Mounting evidence of anomalous observations appear to be supported by other theories, such as prospect theory, which in particular helps explain the disposition effect – sellers are too quick to sell when prices are climbing and hold on to properties longer when prices are plummeting. While this evidence is widely documented in housing studies based on data on realized holding periods (i.e. ex post), this study explores factors that may motivate homeowners to alter their expected holding horizons (i.e. ex ante) to form new preferred holding periods that may be shorter or longer than those planned during house search.

The empirical study uses data collected from two cross-section surveys of recent homebuyers in rising and declining housing markets in Southern California in 2004-2005 and 2007-2008, respectively.

The empirical results demonstrate that in addition to the financial characteristics of the recent homebuyer, the characteristics of the buying experience – non-monetary, such as the realized search duration, and monetary, such as perception of negative or positive premium paid for the house relative to its market value – have a statistically significant effect on the holding horizon revision. The data strongly indicate that the perception of having overpaid increases the likelihood of upward revision of the original holding horizon. This effect is stronger in the declining than in the rising market – a crucial finding that mirrors the disposition effect.

This study sheds new light on what may contribute to the disposition effect in housing markets that has not yet been investigated in past literature. The novel approach here is to look at how different house price environments may affect homeowners’ holding periods ex ante when they begin, rather than ex post when already realized.

The Austrian theory of the business cycle (henceforth ABC) frequently has been a target for critics of Austrian economics. In particular, a number of economists who are generally appreciative of other Austrian themes have singled out ABC as being, in one such critic's words, an “embarrassing excrescence” marring the otherwise generally sound body of modern Austrian thought.¹ Despite such criticisms, many Austrian economists persist in forwarding ABC as the best available, or perhaps even the only valid, explanation for the cycles of boom and bust regularly occurring in most modern, national economies.

This study examines the relationship between economic fluctuations and financial distress in the US agricultural sector, which is associated with a large degree of financial instability.

The authors developed a parsimonious model of economic fluctuations in the US agricultural sector. The authors used statistical filter methods to identify the co-movement in cyclical fluctuations in real, cumulative growth rates in farm real estate values, farm sector debt and leverage.

The proposed model closely approximated the financial evolution of the US agricultural sector between 1960 and 2018. In addition, the authors proved that the proposed model is an early warning indicator of farm loan delinquencies and farm bankruptcies.

This study exploits recent advances in economic theory and empirical macroeconomic modeling to develop a model that is a robust predictor of financial distress in the agricultural sector. Further, the authors demonstrate that the policy interventions following the 1980s farm financial crisis demonstrate the likely long-run economic response to the policies enacted following the 2008 financial crisis.

The experience of the 1990s renewed economists’ interest in the role of credit in macroeconomic fluctuations. The locus classicus of the credit-boom view of economic cycles is the expansion of the 1920s and the Great Depression. In this paper we ask how well quantitative measures of the credit boom phenomenon can explain the uneven expansion of the 1920s and the slump of the 1930s. We complement this macroeconomic analysis with three sectoral studies that shed further light on the explanatory power of the credit boom interpretation: the property market, consumer durables industries, and high-tech sectors. We conclude that the credit boom view provides a useful perspective on both the boom of the 1920s and the subsequent slump. In particular, it directs attention to the role played by the structure of the financial sector and the interaction of finance and innovation. The credit boom and its ultimate impact were especially pronounced where the organization and history of the financial sector led intermediaries to compete aggressively in providing credit. And the impact on financial markets and the economy was particularly evident in countries that saw the development of new network technologies with commercial potential that in practice took considerable time to be realized. In addition, the structure and management of the monetary regime mattered importantly. The procyclical character of the foreign exchange component of global international reserves and the failure of domestic monetary authorities to use stable policy rules to guide the more discretionary approach to monetary management that replaced the more rigid rules-based gold standard of the earlier era are key for explaining the developments in credit markets that helped to set the stage for the Great Depression.

The purpose of this paper is to examine the impacts of fiscal policy, namely, net tax and government expenditure on national saving and its nonlinearity. The author first investigates whether the impacts of fiscal policy on national saving have changed after the global financial crisis of 2008. Then, the author tests the nonlinearity of the relationship by taking account of the economic cycle, namely, economic expansion (boom) and economic recession (bust).

The empirical model bases on a reduced-form equation with national saving as a dependent variable, lagged value of national saving, output gap and fiscal policy as independent variables. The two-step system GMM approach was employed to estimate the empirical model, using a panel of 23 emerging Asian economies in the period of 1990-2015.

The empirical results show that tax policy and expenditure policy follow the predictions of the overlapping generation model with finite horizon and the Keynesian view. The nonlinearity of fiscal policy is twofold. The conduct of fiscal policy in the period after 2008 seems effective, while the effect is insignificant in the period before 2008. Likewise, fiscal policy tends to have more significant effects in bust cycle. The effect of tax policy is increased during recession, while the effect of government spending is more pronounced during economic downturn.

The contributions of this paper are twofold. First, it is shown that fiscal policies in the region had more impacts on national saving after the global financial crisis of 2008. Second, the research confirms nonlinear impact of fiscal policy on saving behavior during economic recession and economic boom.