Ifo Institute Research Articles

Information, Coordination and the Industrialization of Countries

The industrialization process of a country is often plagued by a failure to coordinate investment decisions. Using the Global Games approach we can solve this coordination problem and eliminate the problem of multiple equilibria. We show how appropriate information provision enhances efficiency. We discuss extensions of the model and argue that subsidies may be a property of a signalling equilibrium to overcome credibility problems in information provision. In addition, we point out possible problems with overreaction to public information. Furthermore, we suggest a new focus for development policy. © The Author 2008. Published by Oxford University Press on behalf of Ifo Institute for Economic Research, Munich. All rights reserved.

Qualitative business surveys and the assessment of employment — A case study for Germany

Business tendency surveys are a commonly accepted instrument for the assessment of the current business cycle course. Most of these surveys rely on qualitative questions about the current situation of the firms and about their expectations for the coming months. This paper analyzes whether qualitative questions about employment expectations are useful to assessing actual employment changes. In Germany the Ifo Institute specialises in business surveys. The German Ifo data are investigated using three different approaches: smoothing techniques are used to help in dating turning points in the course of the series; error correction models are used to analyze the general lead/lag relationships and Probit models are used to estimate a threshold for the survey-based indicator which helps to differentiate between an increase and a decrease in employment. All three methods indicate that the employment expectations are a leading indicator of actual employment changes.

Another Look at the Ifo Business Cycle Clock

Business tendency surveys are a popular instrument for business cycle analysis. The survey results are used to calculate leading business cycle indicators. For Germany the Ifo Institute publishes the Ifo business climate, which consists of the results of two questions: one question about the current situation of the respondents and a second question about their expectations for the coming months. The business climate combines the answers on both questions to a single indicator. This indicator is closely watched by the public. To visualize the interactions between the two components behind this indicator, the Ifo Institute developed a graphical representation called the Ifo business cycle clock. This article shows, with the help of circular-linear correlation analysis, that this illustration is indeed valuable. But it also shows that the clock times should be interpreted carefully.

Forecasting Quarterly German GDP at Monthly Intervals Using Monthly Ifo Business Conditions Data

The paper illustrates and evaluates a Kalman filtering method for forecasting German real GDP at monthly intervals. German real GDP is produced at quarterly intervals but analysts and decision makers often want monthly GDP forecasts. Quarterly GDP could be regressed on monthly indicators, which would pick up monthly feedbacks from the indicators to GDP, but would not pick up implicit monthly feedbacks from GDP onto itself or the indicators. An efficient forecasting model which aims to incorporate all significant correlations in monthly-quarterly data should include all significant monthly feedbacks. We do this with estimated VAR(2) models of quarterly GDP and up to three monthly indicator variables, estimated using a Kalman-filtering-based maximum-likelihood estimation method. Following the method, we estimate monthly and quarterly VAR(2) models of quarterly GDP, monthly industrial production, and monthly, current and expected, business conditions. The business conditions variables are produced by the Ifo Institute from its own surveys. We use early in-sample data to estimate models and later out-of-sample data to produce and evaluate forecasts. The monthly maximum-likelihood-estimated models produce monthly GDP forecasts. The Kalman filter is used to compute the likelihood in estimation and to produce forecasts. Generally, the monthly German GDP forecasts from 3 to 24 months ahead are competitive with quarterly German GDP forecasts for the same time-span ahead, produced using the same method and the same data in purely quarterly form. However, the present mixed-frequency method produces monthly GDP forecasts for the first two months of a quarter ahead which are more accurate than one-quarter-ahead GDP forecasts based on the purely-quarterly data. Moreover, quarterly models based on purely-quarterly data generally cannot be transformed into monthly models which produce equally accurate intra-quarterly monthly forecasts.

Financial Constraints for Investors and the Speed of Adaptation: Are Innovators Special?

This paper uses a large panel of survey data on German firms in the manufacturing sector to analyse the effects of financing constraints for investors in general and for innovative firms in particular. Survey data with information on financing conditions are potentially a valuable tool that avoids the Kaplan and Zingales (1997) critique on the use of cash flow sensitivities for the identification of financial constraints. Using the autumn and the spring wave of the Ifo Institute’s Investment Tests (IT) during the years 1988-1998, we create a panel with information on investment, innovation activity and financing conditions. Financial constraints affect the distribution of investment over time in a fundamental way. Following a shock, the adjustment of a constrained firm is slower and less spiky. After developing this argument theoretically building on Schworm’s (1980) model of optimal investment under financial constraints, we use it to test the empirical content of our survey data by means of an error correction model of investment activity. Our preliminary results indicate that constrained firms in fact do react more slowly, but that innovative firms are not especially affected. This supports an argument made by Bond, Harhoff and van Reenen (1999): In equilibrium, innovative activity will come from a group of firms that is self-selected on the basis of their being able to overcome the special difficulties of financing innovation.

Sustainable development revisited

Before one can talk about “sustainability”, economic development has to have occurred, and the traditional motor for development has always been economic growth, says Professor Karl Heinrich Oppenländer, President of the ifo Institute for Economic Research. He poses the questions, Is growth policy the best social policy? Has the social market economy failed because of its ties to economic growth, or has this growth simply been too small? What would a strict adherence to the concept of sustainable development mean? This paper was originally presented at the IIPS 10th Anniversary Symposium, “Transforming the Global Order for the 21st Century,” held in Tokyo on 18–19 May 1998.

The Eastern German Labor Market in Transition: Gross Flow Estimates from Panel Data

This paper investigates the behavior of the eastern German labor market during the initial stages of the transition to a market economy, using information contained in a unique longitudinal survey of eastern German residents taken between November 1990 and November 1991. The study utilizes Markovian flow analysis of worker transitions between labor market states. Steady-state predictions confirm that the labor market will undergo substantial contraction before stabilizing and that job creation will be dominated by the emerging service sector. Multinomial logistic estimates suggest that standard methodologies can have a useful role in the analysis of labor markets in transition. J. Comp. Econom., April 1995, 20(2), pp. 139-170. Institute for Employment Research, Nuremberg; London Business School and Centre for Economic Performance, London School of Economics; Ifo Institute for Economic Research and Centre for Economic Performance, London School of Economics; Centre for Economic Performance, London School of Economics.

How to suppress a lead

According to the findings of Scholer (1994)1 the “Business Climate” developed by the ifo Institute for Economic Research, Munich, cannot be used as a leading indicator for business cycle forecast. This paper shows that this result is due to Scholer's choice of statistical methods applied: apart from generating stationary time series, Scholer's filter systematically suppresses the business cycle components and amplifies the irregular components. It impairs the basis for the causality test.

Success breeds success. The dynamics of the innovation process

This paper presents a dynamic random effects probit model for the realization of private firms’ product and process innovations. We estimate the model with panel data collected by the Ifo Institute in Munich. The data covers the period between 1979 and 1986 and includes 301 firms of the West German manufacturing sector. It turns out that firms’ probabilities of innovation depend on market structure, demand and cost expectations, unobserved heterogeneity, and realized innovations in the previous year. The positive significant influence of past innovations indicates that there is strong state dependence in the innovation process. This result supports the ’success breeds success’ hypothesis suggesting a positive impact of innovative success to further innovations in the following years.

Business climate as a leading indicator? An empirical investigation for west Germany from 1978 to 1990

For twenty-five years now, the leading indicator “Business Climate” of the Ifo Institute has been applied in the Federal Republic of Germany. The intent of this note is to provide answers to two questions by means of econometric methods. The first question is: Is the business climate really a leading indicator? The second question is: How much time is the indicator ahead? For verification and in order to respond to both questions, the Granger causality test is used in the version of Hsiao.

Constructing leading indicators from non-balanced sectoral business survey series

This paper considers the construction of leading indicators based on monthly survey data from the Ifo Institute, Munich. The three main points covered in the paper are: (a) The use of survey data at the sectoral level results in a longer leading indicator. By taking a non-balanced form of the survey answers and exploiting the information contained in ‘no change’ responses through the use of canonical coherence, regressions on certain wave lengths lead to higher cross-spectral coherencies between the survey data and the actual business cycle, (b) Comparisons of frequency domain and time domain results for lead-lag relationships highlight the roles of seasonal and business cycles, (c) Out of sample forecasts reveal that the traditional balance concept is dominated by a weighted average of ‘worse’ and ‘equal’ responses. Surprisingly, the best results come from using the ‘worse’ share.

Innovation spending and productivity growth in the German economy 1980–1986

A newly developed technique involving vertically integrated input-output sectors is used to examine the relationship between labour productivity and innovation expenditures in the German economy during the period 1980 to 1986. The productivity measures used, dubbed Harrod-Robinson-Read (HRR), take into account the direct and indirect labour used in each consumption goods sector. Included in these measures is the labour content of new capital investment. The HRR measures show higher rates of productivity growth in most sectors, compared to the simple direct labour requirements measures. This is due to the fact that the HRR measures take into account the increased efficiency with which new capital is produced. The second part of the study examines the relationship between labour productivity and innovation expenditures as measured by the IFO (Institute for Economic Research – Munich) innovation survey. Using cross section data for 58 German industries, a strong correlation was found between direct labour pr...

Still more on the speed of adjustment in inventory models: A lesson in aggregation

Applied econometric research has been troubled by the fact that estimated adjustment speeds from stock-adjustment models of inventory investment turn out to be “implausibly slow”. The paper presents new empirical evidence using business-survey data colfected by the IFO Institute Munich, Germany. It is shown empirically that there is no such a thing as an “implausibly slow” adjustment speed if estimation is done at the same level of aggregation as is requested by the underlying microeconomic theory, that is, at the level of the individual firm. Slow adjustment speeds turn out to be an artifact due to aggregation.