Analysis and Predictive Methodology for Ceramic Exports 2024

Introduction

This report analyzes Spanish exports of ceramic flooring and wall tiles to Germany during 2024, comparing them with 2023 data. Using a predictive methodology based on time series and seasonal factors, monthly export estimates, confidence intervals (CI), and other key indicators have been projected. The objective is to provide a tool for strategic decision-making in a dynamic market environment. Notably, the data corresponding to December 2024 is a projection based on observed trends and the most recent data.

General Summary

Exports to Germany in 2024 show a reduction of 8.06% compared to 2023, decreasing from 140,879.50 thousand euros to 129,523.06 thousand euros. This decline is influenced by seasonal factors, monthly patterns, and variations in market trends.

Key Data:

December 2024 Forecast (Moving Average):

Estimated Value: 9,860.00 thousand euros.

95% Confidence Interval: [8,847.00; 10,897.00 thousand euros].

This value reflects an estimate based on the previous three months (September, October, and November) and represents the most accurate prediction based on recent data.

Forecast Adjusted by Seasonal Factor:

Estimated Value: 6,525.00 thousand euros.

Note: This value, derived from the specific seasonal factor for December, falls outside the calculated confidence interval range, highlighting its reliance on historical patterns and disconnection from current market dynamics.

Estimated Average Price per Square Meter (M2): 15.05 €/M2.

Total Annual Variation Forecast: -8.06%.

Applied Methodology

Forecasting Models

Moving Average Forecast

To calculate the primary forecast for December 2024, a simple moving average was used, based on the deseasonalized values of the previous three months (September, October, and November). This method effectively captures the most recent trends, making it particularly useful in dynamic markets such as ceramic exports.

Confidence Intervals (CI)

Calculated using Student’s t-distribution to account for uncertainty due to the small sample size (12 months). This analysis used 2 degrees of freedom, which is appropriate for a conservative calculation with a 95% confidence level.

Lower Limit: 8,847.00 thousand euros.

Upper Limit: 10,897.00 thousand euros.

Critical Value of Student’s t: 4.303.

Seasonal Factor Forecast

The seasonal factor-based projection was calculated by adjusting historical exports to the specific December pattern. While this method offers a useful historical perspective, its disconnection from recent trends makes it less relevant in this analysis.

Complementary Variables

Monthly Trend: Calculated as the deseasonalized average.

Residual: Difference between observed values and the deseasonalized trend.

Average price per ton and M2: Key factors in identifying market patterns.

Appendix: Determination of the Trend

Applied Method

Linear Fit:

Model Slope: -846,445.249 €.

Intercept: 53,486,121.8 €.

Slope Interpretation: Indicates an average monthly decline in imports.

Residual Mean: Identifies key deviations in July and December.

Results by Month

January to November:

March: Decrease of -24.02% compared to 2023, explained by lower German demand and price adjustments.

April: Increase of 8.60%, reflecting a slight seasonal recovery.

November: Drop of -22.48%, attributed to market volatility and reductions in export volume.

December Forecast:

Expected Exports: 9,860.00 thousand euros (primary forecast based on moving average).

Alternative Forecast: 6,525.00 thousand euros (based on seasonal factor).

Confidence Interval: [8,847.00; 10,897.00] thousand euros.

Relative Recovery Compared to December 2023: +37.77%, attributed to recent commercial strategies such as an average 7.7% reduction in price/m2.

Conclusion

The analysis highlights a market contraction in 2024, with monthly variations influenced by seasonal patterns and external factors. The employed methodology, prioritizing moving average forecasts and confidence intervals, allows for reliable estimates to support decision-making in logistics, marketing, and strategic planning.

Recommendations:

Market Diversification: Minimize risks associated with dependency on the German market.

Optimization of Promotional Campaigns: Focus on months with seasonal recovery potential.

Constant Monitoring: Adjust strategies based on actual behavior versus projections.