---
ticker: "KRGDPGAP"
title: "South Korea Output Gap"
unit: "%"
frequency: "Quarterly"
source: "Holston, Laubach, and Williams (2023); Hale et al. (2021)"
release: "Updated Quarterly"
category: "National Accounts"
country: "KR"
language: "en"
canonical: "https://kred.dev/en/series/KRGDPGAP"
license: "https://creativecommons.org/licenses/by-nc-nd/4.0/"
latest_value: 0.64
latest_date: "2026-06-30"
first_date: "1997-03-31"
observations_total: 118
observations_shown: 118
---

# South Korea Output Gap

## Overview

Gauges overheating or slack from how far actual output runs above or below potential.

## Key Figures

|  | Value | Date |
|---|---|---|
| Latest | 0.64 | 2026-06-30 |
| Change from previous | +0.13 | 2026-03-31 |
| Change over one year | +1.75 | 2025-06-30 |
| Highest on record | 3.45 | 1997-06-30 |
| Lowest on record | -8.60 | 1998-06-30 |
| Period covered | 1997-03-31 – 2026-06-30 |  |
| Observations | 118 |  |

## Recent observations

| Date | Value | Change |
|---|---|---|
| 1997-03-31 | 1.47 |  |
| 1997-06-30 | 3.45 | +1.98 |
| 1997-09-30 | 3.24 | -0.21 |
| 1997-12-31 | 1.36 | -1.89 |
| 1998-03-31 | -6.40 | -7.76 |
| 1998-06-30 | -8.60 | -2.20 |
| 1998-09-30 | -8.02 | +0.58 |
| 1998-12-31 | -6.83 | +1.19 |
| 1999-03-31 | -5.05 | +1.78 |
| 1999-06-30 | -2.26 | +2.79 |
| 1999-09-30 | -0.75 | +1.51 |
| 1999-12-31 | 0.47 | +1.22 |
| 2000-03-31 | 0.99 | +0.52 |
| 2000-06-30 | 1.07 | +0.07 |
| 2000-09-30 | 2.15 | +1.08 |
| 2000-12-31 | 0.56 | -1.59 |
| 2001-03-31 | 0.08 | -0.48 |
| 2001-06-30 | 0.10 | +0.02 |
| 2001-09-30 | -0.00 | -0.10 |
| 2001-12-31 | 0.15 | +0.15 |
| 2002-03-31 | 1.46 | +1.32 |
| 2002-06-30 | 1.99 | +0.52 |
| 2002-09-30 | 2.51 | +0.52 |
| 2002-12-31 | 2.10 | -0.41 |
| 2003-03-31 | 0.39 | -1.71 |
| 2003-06-30 | -0.75 | -1.14 |
| 2003-09-30 | -0.42 | +0.33 |
| 2003-12-31 | 0.78 | +1.19 |
| 2004-03-31 | 0.97 | +0.20 |
| 2004-06-30 | 0.58 | -0.39 |
| 2004-09-30 | -0.27 | -0.85 |
| 2004-12-31 | -0.64 | -0.37 |
| 2005-03-31 | -0.90 | -0.27 |
| 2005-06-30 | -0.26 | +0.65 |
| 2005-09-30 | -0.02 | +0.23 |
| 2005-12-31 | -0.04 | -0.02 |
| 2006-03-31 | 0.35 | +0.40 |
| 2006-06-30 | -0.05 | -0.41 |
| 2006-09-30 | 0.34 | +0.40 |
| 2006-12-31 | 0.08 | -0.27 |
| 2007-03-31 | 0.71 | +0.63 |
| 2007-06-30 | 1.27 | +0.56 |
| 2007-09-30 | 1.44 | +0.17 |
| 2007-12-31 | 2.35 | +0.91 |
| 2008-03-31 | 2.18 | -0.17 |
| 2008-06-30 | 1.63 | -0.56 |
| 2008-09-30 | 1.26 | -0.36 |
| 2008-12-31 | -2.84 | -4.10 |
| 2009-03-31 | -3.52 | -0.68 |
| 2009-06-30 | -3.04 | +0.48 |
| 2009-09-30 | -1.04 | +1.99 |
| 2009-12-31 | -1.17 | -0.13 |
| 2010-03-31 | 0.07 | +1.24 |
| 2010-06-30 | 0.71 | +0.63 |
| 2010-09-30 | 0.79 | +0.08 |
| 2010-12-31 | 1.23 | +0.44 |
| 2011-03-31 | 1.29 | +0.06 |
| 2011-06-30 | 0.79 | -0.50 |
| 2011-09-30 | 0.39 | -0.40 |
| 2011-12-31 | 0.23 | -0.16 |
| 2012-03-31 | 0.36 | +0.13 |
| 2012-06-30 | -0.02 | -0.39 |
| 2012-09-30 | -0.41 | -0.38 |
| 2012-12-31 | -0.51 | -0.10 |
| 2013-03-31 | -0.52 | -0.01 |
| 2013-06-30 | -0.23 | +0.28 |
| 2013-09-30 | -0.02 | +0.21 |
| 2013-12-31 | 0.09 | +0.11 |
| 2014-03-31 | 0.11 | +0.02 |
| 2014-06-30 | 0.21 | +0.10 |
| 2014-09-30 | -0.23 | -0.44 |
| 2014-12-31 | -0.46 | -0.24 |
| 2015-03-31 | -0.39 | +0.08 |
| 2015-06-30 | -0.72 | -0.34 |
| 2015-09-30 | -0.08 | +0.65 |
| 2015-12-31 | -0.03 | +0.05 |
| 2016-03-31 | -0.36 | -0.33 |
| 2016-06-30 | 0.10 | +0.47 |
| 2016-09-30 | -0.23 | -0.33 |
| 2016-12-31 | -0.18 | +0.05 |
| 2017-03-31 | 0.13 | +0.31 |
| 2017-06-30 | 0.10 | -0.03 |
| 2017-09-30 | 0.67 | +0.57 |
| 2017-12-31 | -0.15 | -0.82 |
| 2018-03-31 | 0.45 | +0.60 |
| 2018-06-30 | 0.53 | +0.08 |
| 2018-09-30 | 0.34 | -0.19 |
| 2018-12-31 | 0.16 | -0.18 |
| 2019-03-31 | -0.45 | -0.61 |
| 2019-06-30 | 0.20 | +0.65 |
| 2019-09-30 | -0.10 | -0.30 |
| 2019-12-31 | 0.23 | +0.33 |
| 2020-03-31 | 0.06 | -0.17 |
| 2020-06-30 | -1.85 | -1.91 |
| 2020-09-30 | -0.38 | +1.47 |
| 2020-12-31 | 0.80 | +1.18 |
| 2021-03-31 | 1.98 | +1.18 |
| 2021-06-30 | 2.26 | +0.28 |
| 2021-09-30 | 1.43 | -0.83 |
| 2021-12-31 | 2.39 | +0.97 |
| 2022-03-31 | 2.32 | -0.07 |
| 2022-06-30 | 1.42 | -0.90 |
| 2022-09-30 | 0.93 | -0.49 |
| 2022-12-31 | -0.08 | -1.01 |
| 2023-03-31 | -0.96 | -0.88 |
| 2023-06-30 | -0.76 | +0.19 |
| 2023-09-30 | -0.26 | +0.50 |
| 2023-12-31 | -0.00 | +0.26 |
| 2024-03-31 | 0.50 | +0.50 |
| 2024-06-30 | -0.09 | -0.59 |
| 2024-09-30 | -0.43 | -0.33 |
| 2024-12-31 | -0.66 | -0.23 |
| 2025-03-31 | -1.25 | -0.60 |
| 2025-06-30 | -1.11 | +0.14 |
| 2025-09-30 | -0.25 | +0.87 |
| 2025-12-31 | -0.70 | -0.45 |
| 2026-03-31 | 0.51 | +1.21 |
| 2026-06-30 | 0.64 | +0.13 |

## Definition

The output gap measures the percentage difference between actual real GDP and the COVID-adjusted level of potential output, capturing the degree of slack or overheating in the economy.

Formally, the output gap $\tilde{y}_t$ is the log level of real GDP minus COVID-adjusted potential output:

$$\tilde{y}_t = y_t - y^{*,COVID}_t$$

where

$$y_t = 100 \times \ln(GDP_t)$$

is the log level of actual real GDP and $y^{*,COVID}_t$ adjusts potential output for the transitory supply disruptions caused by COVID-19 lockdowns.

The COVID adjustment prevents the pandemic-era GDP collapse from being misattributed to a permanent decline in potential output, and is constructed as:

$$y^{*,COVID}_t = y^*_t + (\phi / 100) \cdot d_t$$

where $d_t$ is the OxCGRT Government Stringency Index and $\phi$ is an estimated coefficient capturing the supply-side impact of lockdown measures.

A negative output gap indicates economic slack, where the economy operates below its potential, suggesting underutilized labor and capital resources and downward pressure on inflation through the Phillips curve. A positive output gap indicates overheating, where demand exceeds the economy's sustainable production capacity, with upward pressure on inflation.

The COVID-adjusted output gap reported in this series should be distinguished from the unadjusted output gap $y_t - y^*_t$, which is available as a secondary field in the chart. The unadjusted gap attributes all of the pandemic-era GDP decline to demand deficiency, while the adjusted gap correctly reclassifies the portion attributable to government-mandated supply restrictions.

## Methodology

Estimated jointly with the natural rate of interest ($r^*$, KRNR), trend growth (KRTRGDP), and the real rate gap (KRRRGAP) within the HLW (2023) 3-stage MLE state-space model. The full model specification, data inputs, and estimation procedure are described in detail in the KRNR methodology section; this section highlights the aspects specific to the output gap.

**(1) Output gap within the structural model.** The output gap

$$\tilde{y}_t = y_t - y^*_t$$

is not directly a state variable but is derived as the difference between observed GDP and the Kalman-smoothed estimate of potential output. It enters the IS curve as the dependent variable:

$$\tilde{y}_t = a_{y,1}\,\tilde{y}_{t-1} + a_{y,2}\,\tilde{y}_{t-2} + \dfrac{a_r}{2}\left[(r_{t-1} - r^*_{t-1}) + (r_{t-2} - r^*_{t-2})\right] + \epsilon^{\tilde{y}}_t \tag{IS}$$

It also enters the Phillips curve as a determinant of inflation through the $b_y \tilde{y}_{t-1}$ term, where $b_y > 0$ captures the effect of demand pressures on price dynamics.

**(2) COVID-19 adjustment.** The COVID-adjusted potential output is:

$$y^{*,COVID}_t = y^*_t + (\phi / 100) \cdot d_t$$

where $d_t$ is the quarterly average of the Oxford COVID-19 Government Response Tracker (OxCGRT) Stringency Index for Korea. The stringency index is constructed from daily observations, averaged to quarterly frequency, and zero-padded after the last observed quarter to ensure the adjustment phases out as pandemic restrictions end. The coefficient $\phi < 0$ is freely estimated in Stage 3 of the model, capturing the percentage-point reduction in output per unit increase in the stringency index. Time-varying measurement error variances $\kappa_{2020}$, $\kappa_{2021}$, $\kappa_{2022}$ account for the increased macroeconomic volatility during the pandemic period, and these are freely estimated scale factors that multiply the observation covariance matrix.

**(3) Estimation uncertainty.** The output gap inherits substantial estimation uncertainty from the smoother's estimate of potential output. The standard error is:

$$se(\tilde{y}_t) = se(y^*_t) = \sqrt{P^{smooth}_t[0,0]}$$

since observed GDP is known exactly and all uncertainty resides in $y^*_t$. End-of-sample output gap estimates are particularly unreliable, as the smoother cannot draw on future observations to refine the estimate of current potential output. This is a problem well-documented by Orphanides and van Norden (2002).

## Applications in Economics

The output gap is a core input for monetary policy decisions and macroeconomic assessment, connecting the real side of the economy to inflation dynamics through the Phillips curve.

The output gap enters the Phillips curve in the HLW structural model through the coefficient $b_y$, where a positive gap exerts upward pressure on inflation and a negative gap is disinflationary. This channel is central to the BOK's monetary policy framework, where the central bank estimates the current output gap to assess whether aggregate demand conditions are consistent with the inflation target. The HLW output gap provides a model-consistent estimate that is jointly estimated with the natural rate and trend growth, ensuring internal coherence across the monetary policy assessment variables.

Output gap estimates are subject to significant real-time revision (Orphanides and van Norden 2002). End-of-sample estimates can differ substantially from the final revised values because (i) GDP data are revised multiple times, (ii) the Kalman smoother's estimate of potential output at the end of sample has access to future data in only one direction, and (iii) trend growth estimates are particularly uncertain at the end of sample. Policymakers should treat the latest observation with appropriate caution and compare with alternative output gap measures.

The HLW output gap can be cross-referenced with other estimates. These comprise (i) the Hodrick-Prescott (HP) filter output gap, a purely statistical detrending method widely used in policy institutions; (ii) the production function approach used by the OECD, IMF, and the BOK's own Research Department, which explicitly models labor, capital, and TFP; and (iii) multivariate filter approaches (e.g., IMF's Flexible System methodology). These methods differ in their structural assumptions and can yield materially different point estimates. The HLW approach has the advantage of being grounded in economic theory (the IS-Phillips curve structure) and jointly estimated with the natural rate, but the disadvantage of imposing a specific functional form on the IS curve dynamics.

During 2020–2021, the COVID adjustment significantly affects the output gap estimate. Without the OxCGRT adjustment, the massive GDP decline in the second quarter of 2020 would appear entirely as a demand shortfall, generating an unrealistically large negative output gap and biasing the estimated natural rate. The adjusted gap reclassifies part of the decline as a transitory supply disruption caused by lockdown measures. The parameter $\phi$ quantifies this reclassification, where a more negative $\phi$ implies a larger supply-side attribution. This distinction matters for policy analysis, as supply-driven output declines call for different policy responses than demand-driven declines.

## Applications in Financial Markets

The output gap is a key cyclical indicator for fixed income positioning, credit analysis, and cross-asset allocation.

A large negative output gap typically precedes monetary policy easing and rate cuts as the BOK acts to close the gap and return inflation to target, creating a bullish signal for KTB prices, particularly at the front end of the curve. Conversely, a closing or positive output gap signals the BOK is likely to tighten, favoring defensive positioning. The output gap can be combined with the real rate gap (KRRRGAP) for a more complete policy stance assessment, where a negative output gap combined with a positive real rate gap is a particularly strong easing signal.

The output gap correlates with corporate default rates and credit spreads in the Korean won bond market. Large negative gaps coincide with economic weakness, elevated default risk, and wider spreads on AA- and BBB rated won-denominated corporate bonds. Positive output gaps compress spreads as corporate earnings and cash flows improve. The output gap thus provides a macroeconomic input for credit cycle timing, signaling an underweight in credit risk during large negative gaps and an overweight during positive gaps.

Output gap dynamics may correlate with term premium regime shifts (KRTPCR series). During recessions, which correspond to a large negative output gap, flight-to-quality demand compresses term premiums as investors seek duration. During expansions, which correspond to a positive gap, term premiums tend to rise as inflation uncertainty increases. Monitoring the output gap alongside the term premium weight (KRTPCR10) helps distinguish between yield curve movements driven by growth expectations versus risk premium repricing.

The output gap provides a macro-cyclical timing signal for equity allocation. A closing negative output gap, where the economy recovers toward potential, is typically associated with improving corporate earnings and positive equity market performance, particularly for cyclical sectors. A positive and widening output gap is associated with inflationary pressures and eventual monetary tightening, which tends to be negative for equity valuations after an initial lag.

## Statistical Tests

KRGDPGAP is the Holston-Laubach-Williams output gap, a latent state extracted by a two-sided Kalman filter and RTS smoother. Over 117 quarterly observations from 1997-03-31 to 2026-03-31, its measured serial correlation is dominated by the smoother's gain rather than by the data-generating process, so the object framed here is a persistence summary of the smoothed path and not an integration order of the data.

The integration-order battery is therefore deliberately not run. The augmented unit-root regression of Dickey and Fuller (1979) with the lag augmentation of Said and Dickey (1984), the semiparametric Phillips and Perron (1988) test, the KPSS stationarity test (Kwiatkowski et al. 1992), the efficient GLS-detrended test of Elliott, Rothenberg, and Stock (1996), and the modified M-tests of Ng and Perron (2001) are all excluded, because a symmetric two-sided filter manufactures the persistence an integration test reads and the random-walk-versus-constant character of the latent state is not point-identified by the likelihood (Stock and Watson 1998; Orphanides and van Norden 2002). The level mean-break search of Bai and Perron (1998) is likewise not run, since its asymptotics require a stationary object and the filter-persistent path spuriously segments (Perron 1989).

The matrix-mandated replacement is a descriptive persistence summary labeled as a property of the smoothed series. The lag-one autocorrelation is 0.813 and the implied half-life is 3.34 quarters, a description of how slowly the smoothed path decays that carries no integration-order claim. Because the HLW loader rewrites the full state history on every re-estimation, the smoothed state at any fixed past quarter revises across vintages, and no stored vintage panel exists to quantify the revision magnitude (Orphanides and van Norden 2002).

No order of integration is assigned, by ruling rather than by an inconclusive test. The lag-one coefficient carries the familiar downward small-sample bias near unity, so the half-life is a lower-leaning descriptive figure whose median-unbiased interval would follow the grid of Andrews (1993), and the lag-one autocorrelation a portmanteau such as that of Ljung and Box (1978) would register is a filter-gain reading rather than evidence about the process. The model-implied content is honest as an assumption rather than a discovery, namely a two-sided RTS-smoothed output-gap state, which unlike the one-sided expanding-window credit and house-price gaps that are vintage-invariant by construction revises with every re-smooth and carries the two-sided endpoint unreliability that makes a filtered gap an imperfect real-time gauge (Hamilton 2018; Hodrick and Prescott 1997).

## Frequently Asked Questions

### What are trend potential growth and the output gap?

One is the trend growth rate of potential output, the pace the economy can sustain net of cyclical variation; the other is the output gap, the distance of actual output from that potential level.

### Why is the output gap estimate uncertain?

Potential output is an unobserved state, so the gap is the difference between a measured and an estimated quantity. Potential estimates are revised substantially as later data arrive, and the most recent gap values are the least settled.

### Does a positive output gap mean the economy is overheating?

Not on its own. A positive gap is conventionally read as demand running ahead of capacity, but the estimation uncertainty is wide, so it should be judged alongside direct evidence from prices and the labour market.