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The volatility around financial crises that have hit many middle-income countries (MICs) after they liberalize their financial markets has prompted critics to call for new policies to stabilize these boom-bust cycles. But, as Aaron Tornell and Frank Westermann point out in this book, over the last two decades most of the developing countries that have experienced lending booms and busts have also exhibited the fastest growth among MICs. Countries with more stable credit growth, by contrast, have exhibited, on average, lower growth rates. Factors that contribute to financial fragility thus appear, paradoxically, to be a source of long-run growth as well. Tornell and Westermann analyze boom-bust cycles in the developing world and discuss how these cycles are generated by credit market imperfections. They explain why the financial liberalization that allows countries to overcome imperfections impeding rapid growth also generates the financial fragility that leads to greater volatility and occasional crises. The conceptual framework they present illustrates this linkage and allows Tornell and Westermann to address normative questions regarding liberalization policies. The authors also characterize key macroeconomic regularities observed across MICs, showing that credit markets play a key role not only in boom-bust episodes but in the strong "credit channel" observed during tranquil times. A theoretical framework is then presented that explains how credit market imperfections can account for these empirical patterns. Finally, Tornell and Westermann provide microeconomic evidence on the credit market imperfections that drive the results of the theoretical framework, finding that asymmetries between tradables and nontradables are key to understanding the patterns in MIC data.

We explore the dynamic effects of news about a future technology improvement which turns out ex post to be overoptimistic. We find that it is difficult to generate a boom-bust cycle (a period in which stock prices, consumption, investment and employment all rise and then crash) in response to such a news shock, in a standard real business cycle model. However, a monetized version of the model which stresses sticky wages and a Taylorrule based monetary policy naturally generates a welfare-reducing boom-bust cycle in response to a news shock. We explore the possibility that integrating credit growth into monetary policy may result in improved performance. We discuss the robustness of our analysis to alternative specifications of the labor market, in which wage-setting frictions do not distort on going firm/worker relations.

Growth will slow down next year, but investment and export will help sustain it. The risk of a return to the 'boom‐bust' cycle may not be great now, but is in prospect towards the end of 1990s.

Chapter 1. The market economy: a SWOT analysis -- Chapter 2. The ABCs of the boom-bust cycle -- Chapter 3. How to identify the end of the boom and the bottom of the bust -- Chapter 4. Wash, rinse, repeat: does the past determine our economic future? -- Chapter 5. Managing the supply chain -- Chapter 6. Strengthening the workforce -- Chapter 7. Expansions, mergers, and other opportunities -- Chapter 8. Small business -- Chapter 9. International cyclical impacts on multinationals and small businesses -- Chapter 10. Future economic trends: innovators, disruption, cycles, and the threat of stagnation.

We provide systematic evidence for the association of liquidity shocks and aggregate asset prices during mechanically identified asset price boom/bust episodes for 18 OECD countries since the 1970s, while taking care of the endogeneity of money and credit. Our derivation of liquidity shocks allows for frequent shifts in velocity as they are derived as structural shocks from VARs in growth rates. Residential property price developments and money growth shocks accumulated over the boom periods are able to well explain the depth of post-boom recessions. We further suggest that liquidity shocks are a driving factor for real estate prices during boom episodes. During normal times however, the relative predictive power of liquidity shocks seems to shift from asset price inflation to consumer price inflation. The results only hold for broad money growth based liquidity shocks and not for private credit growth shocks.