Hungary quarterly economic dataset (Q1 2015–Q4 2024)
Description
This dataset contains a quarterly macro-financial panel for Hungary covering the period Q1 2015–Q4 2024 (40 observations). It was constructed to support the empirical analysis in “Equity Risk Premium in Hungary’s Emerging Market: Evaluating Country Risk and Financial Dynamics” and is used to examine the drivers of Hungary’s equity risk premium (ERP). The dataset includes the following variables: Equity Risk Premium (ERP), Expected Equity Return, GDP growth, inflation (CPI), short-term interest rate (Hungarian central bank base rate / 3-month benchmark), 10-year government bond yield, and the Global Volatility Index (VIX, quarterly average). All rates are expressed in percentage terms, while VIX is reported in index points. The ERP is defined consistently with the empirical model as the difference between the expected equity return and the 10-year government bond yield (ERP = Expected Equity Return − 10Y Yield). Expected equity return is correspondingly constructed as the sum of ERP and the 10-year yield. This definitional relationship explains the strong valuation-based dynamics observed in the regression analysis. Data were compiled from official and widely used sources, including the Hungarian Central Statistical Office (KSH), the Magyar Nemzeti Bank (MNB), the CBOE (VIX), and market-based calculations informed by Damodaran’s country risk framework. The dataset contains no missing values and is suitable for replication and further research on equity risk premia, sovereign risk, and valuation dynamics in emerging European markets.
Files
Steps to reproduce
1. Download the dataset Hungary Quarterly Economic Dataset (Q1 2015–Q4 2024) from Mendeley Data and open it in any standard statistical software (e.g., Stata, R, Python, EViews, or Excel). 2. Verify variable construction: a. Confirm that the Equity Risk Premium (ERP) equals the difference between Expected Equity Return and the 10-year government bond yield for each quarter (ERP = ExpRet − 10Y Yield). b. Confirm that Expected Equity Return equals the sum of ERP and the 10-year bond yield. 3. Restrict the sample to the full period Q1 2015–Q4 2024 (40 quarterly observations), as provided in the dataset. No additional filtering or transformations are required. 4. Compute descriptive statistics (mean, median, minimum, maximum) for all variables to replicate the summary statistics reported in the manuscript. 5. Estimate the following Ordinary Least Squares (OLS) regression using contemporaneous quarterly data: ERPₜ = α + β₁·GDP_Growthₜ + β₂·Inflationₜ + β₃·Short_TermRateₜ + β₄·Bond_Yieldₜ + β₅·VIXₜ + β₆·Expected_Returnₜ + εₜ. Use heteroskedasticity-consistent (White) standard errors. 6. Confirm that the coefficients on Expected Equity Return and the 10-year bond yield are approximately +1 and −1, respectively, and that the adjusted R² is close to 1.00, reflecting the definitional relationship between ERP and its valuation components. 7. Replicate figures by plotting the ERP time series and key macro-financial variables over the sample period using quarterly frequency. No external data, additional assumptions, or proprietary code are required to reproduce the results.
Institutions
- Universita Ca' Foscari Dipartimento di ManagementVeneto, Venezia