In accordance with its statutes, the Halle Institute for Economic Research (IWH) pursues an intensive bilateral knowledge transfer on the basis of excellent scientific research with its partners in the non-academic community. In so doing, the IWH contributes to better informed decision making on a societal level. The overarching goal is to foster mutually beneficial exchanges that involve the provision of evidence-based knowledge to society (transfer from the academic to the non-academic community) and the integration of questions of public interest into its research agenda (transfer from the non-academic to the academic community).

We propose a macroeconomic model with a nonlinear Phillips curve that has a flat slope when inflationary pressures are subdued and steepens when inflationary pressures are elevated. The nonlinear Phillips curve in our model arises due to a quasi-kinked demand schedule for goods produced by firms. Our model can jointly account for the modest decline in inflation during the Great Recession and the surge in inflation during the post-COVID period. Because our model implies a stronger transmission of shocks when inflation is high, it generates conditional heteroskedasticity in inflation and inflation risk. Hence, our model can generate more sizeable inflation surges due to cost-push and demand shocks than a standard linearized model. Finally, our model implies that the central bank faces a more severe trade-off between inflation and output stabilization when inflation is elevated.

Using data from the European Central Bank's Survey of Professional Forecasters and ECB/Eurosystem staff projections, we analyze the role of ex-ante conditioning variables for macroeconomic forecasts. In particular, we test to which extent the updating and ex-post performance of predictions for inflation, real GDP growth and unemployment are related to beliefs about future oil prices, exchange rates, interest rates and wage growth. While oil price and exchange rate predictions are updated more frequently than macroeconomic forecasts, the opposite is true for interest rate and wage growth expectations. Beliefs about future inflation are closely associated with oil price expectations, whereas expected interest rates are related to predictions of output growth and unemployment. Exchange rate predictions also matter for macroeconomic forecasts, albeit less so than the other variables. With regard to forecast errors, wage growth and GDP growth closely comove, but only during the period when interest rates are at the effective zero lower bound.

Russian monetary policy has been challenged by large and continuous private capital outflows and a sharp drop in oil prices during 2014. Both contributed to significant depreciation pressures on the ruble and led the central bank to give up its exchange rate management strategy. Against this background, this work estimates a small open economy model for Russia, featuring an oil price sector and extended by a specification of the foreign exchange market to correctly account for systematic central bank interventions. We find that shocks to the oil price and private capital flows substantially affect domestic variables such as inflation and output. Simulations for the estimated actual strategy and alternative regimes suggest that the vulnerability of the Russian economy to external shocks can substantially be lowered by adopting some form of inflation targeting. Strategies to target the nominal exchange rate or the ruble price of oil prove to be inferior.

Real estate markets are pivotal to financial stability given their dual role as the underlying asset of crucial financial products in financial systems, such as mortgage loans and asset-backed securities, and the primary source of household wealth alike. As such, they also play traditionally a crucial role for the transmission of monetary policy. Imbalances and sudden corrections in real estate markets have been the root cause of many financial crises over the last decades. But whereas some national, often survey-based indicators of real estate prices are provided by central banks and statistical offices, a comprehensive collection of purchase prices, rents, and proxies for the liquidity of European real estate markets is lacking. The IWH European Real Estate Index (EREI) seeks to fill this void for residential property. This technical report describes the gathering and processing of sale and rental prices for properties in 18 European countries. We provide the general scrapeing step in the section before describing country-specific details for each country in separated sub-sections.

The economy is a complex system because market participants do not act independently but adjust their behavior to other agents and to the outcome which emerges from their joint actions (Arthur, 2014). Dependencies among participants can impede policy makers capabilities to influence or steer the course of the economy. Kambhu et al. (2007) argue that to influence developments in financial markets, for instance to prevent crises from spreading, there are only “coarse or indirect options” available for policy makers. Similar to crises which propagate through a complex system, interventions might result in unintended side effects which can also disseminate through the system. Thus, in a complex system, unintended consequences of policy efforts may well be the rule. Policy makers try to ward off or mitigate negative consequences for the economy and society during periods of crisis. For instance, during the Covid crisis large scale support programs for firms in Western economies were set up to avoid bankruptcies. Similarly, during the sovereign debt crisis in the Eurozone, the European Central Bank (ECB) set up large scale asset purchase programs as well as additionally longer-term refinancing operations (LTRO) which provided immediate support to financial market participants’ liquidity positions and thereby prevented a melt-down of the financial system. During these periods, immediate and abundant liquidity supply is of utmost importance. Meanwhile, crisis measures, due to their massive scale and non-specific target group, may entail unknown or unintended side effects for instance on competition among market participants, firms’ investment behavior, or changes in lending strategies and risk taking behavior of banks. Likewise, new regulatory frameworks such as the introduction of new markets can have consequences previously not thought of. For policy makers it is important to know direct effects of policy interventions but also to be aware of the possibility and impact of indirect or unexpected side effects in order to evaluate measures taken and to learn for future design of regulation or intervention.

Prognosemodelle für die zukünftige wirtschaftliche Entwicklung verwenden häufig marktbasierte Indikatoren wie Spreads von Unternehmensanleihen, die den Risikoaufschlag gegenüber einem Referenzzins angeben. Anleihespreads bilden jedoch nur die Entwicklung von Risiken für Unternehmen ab, die regelmäßig Anleihen emittieren – im Durchschnitt größere, sichere Firmen. Neuartige Daten zu Bankkrediten, die im Sekundärmarkt gehandelt werden, erlauben auch die Konstruktion von Kreditspreads. Kreditmarktdaten umfassen ein breiteres Spektrum an Firmen, inklusive kleinerer Firmen, die stärker von Finanzmarktfriktionen betroffen sind. Tests zeigen, dass Kreditspreads tatsächlich mehr Informationen über wirtschaftliche Entwicklungen beinhalten als Anleihespreads und daher das Potenzial haben, Prognosemodelle zu verbessern.