Again and again, Latin America has seen the populist scenario played to an unfortunate end. Upon gaining power, populist governments attempt to revive the economy through massive spending. After an initial recovery, inflation reemerges and the government responds with wage an price controls. Shortages, overvaluation, burgeoning deficits, and capital flight soon precipitate economic crisis, with a subsequent collapse of the populist regime. The lessons of this experience are especially valuable for countries in Eastern Europe, as they face major political and economic decisions. Economists and political scientists from the United States and Latin America detail in this volume how and why such programs go wrong and what leads policymakers to repeatedly adopt these policies despite a history of failure. Authors examine this pattern in Argentina, Brazil, Chile, Mexico, Nicaragua, and Peru—and show how Colombia managed to avoid it. Despite differences in how each country implemented its policies, the macroeconomic consequences were remarkably similar. Scholars of Latin America will find this work a valuable resource, offering a distinctive macroeconomic perspective on the continuing controversy over the dynamics of populism.
We test the effect of foreign direct investment (FDI) on economic growth in a cross-country regression framework, utilizing data on FDI flows from industrial countries to 69 developing countries over the last two decades. Our results suggest that FDI is an important vehicle for the transfer of technology, contributing relatively more to growth than domestic investment. However, the higher productivity of FDI holds only when the host country has a minimum threshold stock of human capital. In addition, FDI has the effect of increasing total investment in the economy more than one for one, which suggests the predominance of complementarity effects with domestic firms.
This paper presents a novel approach to investigate and model the network of euro area banks’ large exposures within the global banking system. Drawing on a unique dataset, the paper documents the degree of interconnectedness and systemic risk of the euro area banking system based on bilateral linkages. We develop a Contagion Mapping model fully calibrated with bank-level data to study the contagion potential of an exogenous shock via credit and funding risks. We find that tipping points shifting the euro area banking system from a less vulnerable state to a highly vulnerable state are a non-linear function of the combination of network structures and bank-specific characteristics.
The volatility of capital flows to emerging markets continues to pose challenges to policymakers. In this paper, we propose a new framework to answer critical policy questions: What policies and policy frameworks are most effective in dampening sharp capital flow movements in response to global shocks? What are the near- versus medium-term trade-offs of different policies? We tackle these questions using a quantile regression framework to predict the entire future probability distribution of capital flows to emerging markets, based on current domestic structural characteristics, policies, and global financial conditions. This new approach allows policymakers to quantify capital flows risks and evaluate policy tools to mitigate them, thus building the foundation of a risk management framework for capital flows.
This paper develops a model based on Schumpeter's process of creative destruction. It departs from existing models of endogenous growth in emphasizing obsolescence of old technologies induced by the accumulation of knowledge and the resulting process or industrial innovations. This has both positive and normative implications for growth. In positive terms, the prospect of a high level of research in the future can deter research today by threatening the fruits of that research with rapid obsolescence. In normative terms, obsolescence creates a negative externality from innovations, and hence a tendency for laissez-faire economies to generate too many innovations, i.e too much growth. This "business-stealing" effect is partly compensated by the fact that innovations tend to be too small under laissez-faire. The model possesses a unique balanced growth equilibrium in which the log of GNP follows a random walk with drift. The size of the drift is the average growth rate of the economy and it is endogenous to the model ; in particular it depends on the size and likelihood of innovations resulting from research and also on the degree of market power available to an innovator.
The book provides a comprehensive overview of the latest econometric methods for studying the dynamics of macroeconomic and financial time series. It examines alternative methodological approaches and concepts, including quantile spectra and co-spectra, and explores topics such as non-linear and non-stationary behavior, stochastic volatility models, and the econometrics of commodity markets and globalization. Furthermore, it demonstrates the application of recent techniques in various fields: in the frequency domain, in the analysis of persistent dynamics, in the estimation of state space models and new classes of volatility models. The book is divided into two parts: The first part applies econometrics to the field of macroeconomics, discussing trend/cycle decomposition, growth analysis, monetary policy and international trade. The second part applies econometrics to a wide range of topics in financial economics, including price dynamics in equity, commodity and foreign exchange markets and portfolio analysis. The book is essential reading for scholars, students, and practitioners in government and financial institutions interested in applying recent econometric time series methods to financial and economic data.
Introduction.Big data for twenty-first-century economic statistics: the future is now /Katharine G. Abraham, Ron S. Jarmin, Brian C. Moyer, and Matthew D. Shapiro --Toward comprehensive use of big data in economic statistics.Reengineering key national economic indicators /Gabriel Ehrlich, John Haltiwanger, Ron S. Jarmin, David Johnson, and Matthew D. Shapiro ;Big data in the US consumer price index: experiences and plans /Crystal G. Konny, Brendan K. Williams, and David M. Friedman ;Improving retail trade data products using alternative data sources /Rebecca J. Hutchinson ;From transaction data to economic statistics: constructing real-time, high-frequency, geographic measures of consumer spending /Aditya Aladangady, Shifrah Aron-Dine, Wendy Dunn, Laura Feiveson, Paul Lengermann, and Claudia Sahm ;Improving the accuracy of economic measurement with multiple data sources: the case of payroll employment data /Tomaz Cajner, Leland D. Crane, Ryan A. Decker, Adrian Hamins-Puertolas, and Christopher Kurz --Uses of big data for classification.Transforming naturally occurring text data into economic statistics: the case of online job vacancy postings /Arthur Turrell, Bradley Speigner, Jyldyz Djumalieva, David Copple, and James Thurgood ;Automating response evaluation for franchising questions on the 2017 economic census /Joseph Staudt, Yifang Wei, Lisa Singh, Shawn Klimek, J. Bradford Jensen, and Andrew Baer ;Using public data to generate industrial classification codes /John Cuffe, Sudip Bhattacharjee, Ugochukwu Etudo, Justin C. Smith, Nevada Basdeo, Nathaniel Burbank, and Shawn R. Roberts --Uses of big data for sectoral measurement.Nowcasting the local economy: using Yelp data to measure economic activity /Edward L. Glaeser, Hyunjin Kim, and Michael Luca ;Unit values for import and export price indexes: a proof of concept /Don A. Fast and Susan E. Fleck ;Quantifying productivity growth in the delivery of important episodes of care within the Medicare program using insurance claims and administrative data /John A. Romley, Abe Dunn, Dana Goldman, and Neeraj Sood ;Valuing housing services in the era of big data: a user cost approach leveraging Zillow microdata /Marina Gindelsky, Jeremy G. Moulton, and Scott A. Wentland --Methodological challenges and advances.Off to the races: a comparison of machine learning and alternative data for predicting economic indicators /Jeffrey C. Chen, Abe Dunn, Kyle Hood, Alexander Driessen, and Andrea Batch ;A machine learning analysis of seasonal and cyclical sales in weekly scanner data /Rishab Guha and Serena Ng ;Estimating the benefits of new products /W. Erwin Diewert and Robert C. Feenstra.
Why should radicals be interested in playing wargames? Surely the Left can have no interest in such militarist fantasies? Yet, Guy Debord - the leader of the Situationist International - placed such importance on his invention of The Game of War described it as his most significant of his accomplishment. Intrigued by this claim, a multinational group of artists, activists and academics formed Class Wargames to investigate the political and strategic lessons that could be learnt from playing his ludic experiment. While the ideas of the Situationists continue to be highly influential in the development of subversive art and politics, relatively little attention has been paid to their strategic orientation. Determined to correct this deficiency, Class Wargames is committed to exploring how Debord used the metaphor of the Napoleonic battlefield to propagate a Situationist analysis of modern culture and politics. Inspired by his example its members have also hacked other military simulations: H.G. Wells' Little Wars; Chris Peers' Reds versus Reds and Richard Borg's Commands & Colors. Playing wargames is not a diversion from politics: it is the training ground of tomorrow's communist insurgents. Fusing together historical research on avant-garde artists, political revolutionaries and military theorists with narratives of five years of public performances, Class Wargames provides a strategic and tactical manual for subverting the economic, political and ideological hierarchies of early-21st century neoliberal capitalism. The knowledge required to create a truly human civilisation is there to be discovered on the game board!
