Skip to main content
European Commission logo print header



Economic theory generally suggests that optimal fiscal policy should follow a countercyclical pattern with respect to the business cycles. Namely, if a government respected these prescriptions, the optimal fiscal policy should have a budget surplus in “good times” and a budget deficit in “bad
times”. However, contrary to the theory, a number of recent contributions found evidence that even though fiscal policy in most high-income countries is countercyclical, in many developing countries it is procyclical. In this project, we have empirically and theoretically shown that informality is an important determinant of cyclical behavior of informality. Specifically, we observe that in countries where the informal sector is larger, the procyclicality of fiscal policy is more pronounced. Therefore, governments and policy-makers that aim to make their fiscal policy more countercyclical (as suggested by the theory of optimal fiscal policy) should develop measures and policies to reduce the size of their informal economies.

The project aimed to develop an economic model using the state of the art techniques of dynamic macroeconomics that incorporates fiscal policy and informal economy. This model was then used to analyze various effects of the presence of an informal sector in European countries, specifically how it affects the cyclicality of fiscal policy and thereby economic growth and aggregate productivity over the business cycle. The project was designed attain the following objectives in the analysis of the relationship between the size of the informal sector and cyclicality of fiscal policy:

1) Collection and arrangement of the data on informality and fiscal policy
2) Conducting the empirical analysis using the tools of dynamic panel data econometrics
3) Building a theoretical model to understand the economic mechanism behind the observations established in the second stage

When proposing the project, we planned to work on the project in three phases in line with the three objectives stated above. When the periodic report was submitted the first two phases had been completed. After the first periodic report, the third phase has been completed.

Phase 1 – Collecting and Organizing the Data:
In order to understand the effects of informality on fiscal policy, productivity and growth, we needed to find data on several key variables. First, for the fiscal policy, we used Government Finance Statistics of the IMF, (First, we purchased the right to access to it) OECD Database, World Development Indicators, and Eurostat to collect data on the ratios of government budget deficit, government expenditures, tax revenues, transfer spending and public debt to the GDP. Second, a panel data of the informal sector size (as percentage of GDP) for 162 countries between 1999 and
2007 is available in Schneider (2010). We extended this dataset and constructed a dataset of informal sector size over a large time span, such as 1950-2012 for European countries can also be estimated using various well established techniques. Third, data on other variables to be used in the empirical analysis such as GDP, institutional control variables such as law enforcement, tax enforcement, and bureaucratic quality indices are obtained without much hassle. Data on GDP was already available in various sources, such as the ones counted above or alternatively in Penn World Tables.

Phase 2 – Performing the Empirical Analysis:
In this phase we subjected the data to a batter of econometric tests: instrumental variables, simultaneous equations, system estimation and dynamic panel data estimation methods. In addition, using the data collected in the first phase as well as the empirical specifications developed in the
second phase, Dr. Elgin has supervised two master theses that were completed in June 2012 and then yet another two that were completed in June 2013 and finally then two more that were completed in June 2014.

The first thesis was on the construction of a new methodology to estimate shadow economy size. With the help of this methodology, Dr. Elgin and his advisee was able to extend the size of the informal sector dataset. The second thesis was on the development of a theoretical model that might
shed light on the model we constructed in Phase 3. The two theses that were completed in June 2013 were using the dataset constructed in the previous year and applied to different dimensions of economy policy to investigate growth and business cycle effects of informality. Finally, the last two theses investigated the effects of informality on monetary policy and environmental pollution. Currently, Dr. Elgin supervises yet another masters thesis using the constucted data on "Convergence Effects of Informality".

In Phase 3, that is “Building and Solving the Economic Model", the model was built and numerically solved, and its parameters are calibrated to match certain moments we observe in the data. Next, the model was simulated using the calibrated parameters. This allowed to compare the endogenously determined relationships in the model, such as cyclicality of fiscal policy vs. informal sector size, growth vs. informal sector size and aggregate productivity vs. informal sector size against their data counterparts. Moreover, various comparative static exercises were also performed using the model simulations. One example in these exercises checked the effects of increasing the tax enforcement on the informal sector by increasing the fraction of the tax rate the informal sector pays. It is observed that this policy improvement reduces the informal sector size, makes the fiscal policy less procyclical and thereby increases growth and aggregate productivity; this would be a beneficial recommendation
for policy makers.

The project has produced several already-published papers, as well as some forthcoming ones. A list of these has been made available in the final report and we suggest the interested reader to read these papers for details of our empirical and theoretical results.

Contact details:
Asst. Prof. Ceyhun Elgin
Department of Economics,
Bogazici University,
Bebek, Istanbul TR-34342, Turkey