These are the economic consequences of North Korea's threats

Kim Jong Un’s dictatorship has grabbed the attention of the whole world with its nuclear brinkmanship. On 28 July, it tested an intercontinental ballistic missile that could hit Los Angeles. The North Korean dictator threatened to target Guam, the US territory, with a missile. On 29 August, it fired a ballistic missile, Hwasong-12, over Japan. The launch prompted a stark warning from China that tensions on the Korean peninsula had reached a ‘tipping point’.

US President Donald Trump stated that all options to respond to North Korea are on the table. Mr Trump said in the statement released by the White House: “The world has received North Korea’s latest message loud and clear: this regime has signalled its contempt for its neighbours, for all members of the United Nations, and for minimum standards of acceptable international behaviour”.

Global markets reacted to the escalation in tensions, buying safe-haven assets such as gold, the Swiss franc and the Japanese yen, and selling stocks. Japan's Nikkei 225 index fell almost 1% to a near four-month low, while South Korea's KOSPI index was down by a similar percentage.

In recent work, we show that such escalation in tensions can also have real effects for the US economy in the short to medium run (Ben Zeev and Pappa 2017). We show that announced changes in US public spending on defence have a significant impact on the economic behaviour of firms and households.

In particular, anticipated increases in defence spending induce a significant and persistent increase in output, hours worked, the interest rate and inflation, as well as significant impact responses for consumption and investment. A key characteristic of such shocks is that they increase the excess returns of military contractors long before the actual increase in defence spending is realised.

There has recently been a renewed interest in theories of expectation-driven business cycles, focusing especially on the effects of news shocks: shocks that are realised and observed before they materialise. These types of shocks are of certain importance for fiscal variables, where there is a natural lag between policy decisions and implementation.

Studies that attempt to measure the effects of news shocks empirically have so far used narrative identification of expectational shocks. This methodology, though, is time-consuming to implement, and requires the availability of detailed historical records. Our research proposes an alternative methodology to identify fiscal news in the data, which is easier to implement and can be used in situations where narrative evidence is unavailable.

By its nature, measuring news in the data can be difficult, but in recent years some studies have identified news using the timing of specific events in the context of fiscal changes. A study by Valerie Ramey (2011) constructs two measures of news about changes in defence spending:

The first uses narrative evidence, based on information in Businessweek and other newspapers, to construct an estimate of the change in the expected present value of government spending.The second is constructed using the Survey of Professional Forecasters: changes in government spending are measured as the difference between actual government spending growth and the one-quarter-ahead forecast of government spending growth.

Our approach is different. It identifies defence news shocks as the shocks that best explain future movements in defence spending over a horizon of five years, and which are orthogonal to current defence spending. In other words, using the defence spending series, which are assumed to be exogenous to the state of the economy, we characterise as defence spending news any disturbances that can forecast defence spending movements in five years, but do not relate to current movements in defence spending. We call our shock series MFEV, which is an abbreviation for maximum forecast error variance shocks.

The identified defence news shocks are correlated with the news shocks of Ramey (2011), but explain a much larger fraction of the variability in all real variables at business cycle frequencies. They also generate more significant demand effects by inducing significant and persistent increases in output, hours worked, the interest rate, and inflation. The identified shock using this methodology significantly increases the excess returns of large defence contractors, while Ramey's news shock does not. According to the estimates, news about future changes in defence spending accounts for a non-negligible share of US output fluctuations at business cycle frequencies.

An important contribution of our methodology is that it allows the estimation of the effects of defence news shocks even in the absence of narrative-based measures. Given that such measures are unavailable for most countries, and extremely time-consuming to produce, it is important to show how our empirical results compare with the ones of Ramey (2011). We do so in Figure 1, where we plot the two different shock series from a historical perspective, and try to compare the events that the two shock series capture.

Notes: In order to make the series comparable, since the MFEV series is continuous, while Ramey’s shocks are not, we generated a series that is equal to zero if the corresponding MFEV value is less than one standard deviation in absolute value, and is equal to the MFEV value otherwise. The series begins in 1948:Q1 and ends in 2007:Q4. The series shown by the solid line is the raw Ramey (2011) news series.

The Ramey news and our generated series coincide at only eight points: 1950:Q2, 1961:Q2, 1961:Q4, 1963:Q3, 1977:Q3, 1980:Q2, 1989:Q4 and 2002:Q1. Even for these events, the size of the shock recovered is very different. In 32 cases, Ramey (2011) identifies a news shock that the MFEV methodology fails to capture, and in 24 cases we recover a defence news shock when the Ramey shock is zero.

Some of this mismatch is due to the different timing of the shocks. In five cases, the defence news shock according to the MFEV methodology occurs a few quarters before the Ramey shock. For example, Ramey (2011) identifies a defence news shock in the first quarter of 1981, when Ronald Reagan announced on the 19th of February that he planned to increase the military budget by 24.1%. Instead, the MFEV methodology identifies a shock in the last quarter of 1980, when Reagan was elected and, according to the Republican platform of the 1980 election, an increase in military spending was expected.

Similarly, we recover a news shock in the first quarter of 1990, when tensions between Iraq and Kuwait were increasing and the Iraqi military began preparations at the border with Kuwait, while Ramey (2011) identifies a shock in the fourth quarter of 1990, based on the newspaper reports of US intervention to defend Kuwait.

These discrepancies suggest that the informational content of the two shock series is different. The MFEV shock we recover can be thought of as having two components: one that is closely related to the Ramey news and corresponds to information that was available in the public sphere about future changes in defence spending, and one that is unrelated to this information and the MFEV methodology is extracting by exploiting the Forecast error variance decomposition of defence spending. Ramey news may, or may not, have actually been implemented.

Instead, by construction, the MFEV news shocks relate to defence news that were all implemented, but it is less clear whether they were in the public sphere. It could be that they were in the news and Ramey failed to capture them, or judged that they were not relevant for forecasting future changes in defence.

What is important is that the defence news shocks we identify increase on impact the excess returns of large US military contractors. Thus, according to Ramey’s methodology, the latest provocations of Kim and Trump’s responses to them could be considered news about future increases in defence spending in the US, and according to our methodology this news could be ‘real’ defence news if they are combined with increases in the returns of US military contractors. In such case, North Korea’s insistent and rapid test-firing missiles could paradoxically boost, according to our findings, the US economy.

We conclude by suggesting that policymakers should be cautious about announcing policy changes that can affect people’s expectations about future government spending. Or, reversing this argument, policymakers can use policy announcements as a tool for responding to the cycle when constrained by budgetary or other types of restrictions.

References

Ben Zeev, N and E Pappa (2017), ‘Chronicle of a War Foretold: The Macroeconomic Effects of Anticipated Defence Spending Shocks’, Economic Journal 127: 1568-97.

Ramey, V A (2011), ‘Identifying Government Spending Shocks: It’s All in the Timing’, Quarterly Journal of Economics 126(1): 1-50.