## Explaining Inflation in Colombia: A Disaggregated Phillips Curve Approach

_IMF Working Papers, May 10, 2018_

## Source details

**Canonical URL:** [Explaining Inflation in Colombia: A Disaggregated Phillips Curve Approach](https://www.imf.org/en/publications/wp/issues/2018/05/10/explaining-inflation-in-colombia-a-disaggregated-phillips-curve-approach-45850)

## Other formats

- [Markdown version](/en/publications/wp/issues/2018/05/10/explaining-inflation-in-colombia-a-disaggregated-phillips-curve-approach-45850/index.md)
- [Structured JSON version](/en/publications/wp/issues/2018/05/10/explaining-inflation-in-colombia-a-disaggregated-phillips-curve-approach-45850/index.json)
- [Bundle manifest](/en/publications/wp/issues/2018/05/10/explaining-inflation-in-colombia-a-disaggregated-phillips-curve-approach-45850/bundle-manifest.json)

## Bibliographic details
- Authors: Sergi Lanau, Adrian Robles, Frederik G Toscani
- Published: May 10, 2018
- Series: IMF Working Papers
- DOI: https://doi.org/10.5089/9781484354827.001

---

### Main findings
- The study uses a bottom-up Phillips curve approach to capture drivers of individual inflation components.
- The Phillips curve is relatively flat in Colombia but steeper than recent estimates for the U.S.
- Supply side shocks play an important role for tradable and food prices.
- Indexation dynamics are important for non-tradable goods.
- The bottom-up approach improves on an aggregate Phillips curve in terms of forecasting ability.
- In the baseline forecast scenario, both headline and core inflation converge towards the Central Bank’s inflation target of 3 percent by end-2018.
- These favorable inflation dynamics are vulnerable to large supply shocks.

### Methodology and scope
- Approach: bottom-up (disaggregated) Phillips curve estimation to analyze individual inflation components.
- Focus areas: tradable inflation, food inflation, non-tradable goods inflation, indexation dynamics, supply side shocks, output gap effects, inflation expectations.

### Forecasts, scenarios, and vulnerabilities
- Baseline forecast outcome: headline and core inflation converge to 3 percent by end-2018.
- Vulnerability highlighted: large supply shocks can derail convergence implied by the baseline forecast.

### Policy-relevant implications
- Disaggregated modeling provides a more detailed understanding of inflation drivers than aggregate Phillips curve models and yields improved forecasting ability.
- Attention to supply side developments is critical for managing tradable and food price inflation.
- Monitoring indexation mechanisms is important for understanding and addressing non-tradable goods inflation.
- Monetary policy and macroeconomic frameworks should consider the potential for large supply shocks when assessing inflation outlooks.

*Source: Explaining Inflation in Colombia: A Disaggregated Phillips Curve Approach, Sergi Lanau, Adrian Robles, Frederik G Toscani, May 10, 2018.*

---

## Content in this bundle

- **Explaining Inflation in Colombia: A Disaggregated Phillips Curve Approach, WP/18/106, May 2018**
  - [Explaining Inflation in Colombia: A Disaggregated Phillips Curve Approach, WP/18/106, May 2018 (Markdown version)](/-/media/files/publications/wp/2018/wp18106.pdf.md){rel="alternate" type="text/markdown"}
  - [Explaining Inflation in Colombia: A Disaggregated Phillips Curve Approach, WP/18/106, May 2018 (PDF)](/-/media/files/publications/wp/2018/wp18106.pdf){rel="external" type="application/pdf"}

---

_Source: https://www.imf.org/en/publications/wp/issues/2018/05/10/explaining-inflation-in-colombia-a-disaggregated-phillips-curve-approach-45850_