The Effects of Sanctions on North Korean Food Prices: Evidence from Pyongyang
Markets
Justin V. Hastings
Department of Government and International Relations
Merewether (H04)
University of Sydney NSW 2006
AUSTRALIA
[email protected]
Phone: +61 466 986 575
Fax: +61 2 9351 3624]
(Corresponding author)
David Ubilava
School of Economics
Merewether (H04)
University of Sydney NSW 2006
AUSTRALIA
[email protected]
Yaohui Wang
University of Sydney
Apartment 501, Building 93-2, 93 Jinshan road
Shenyang, Liaoning 110000
PEOPLE’S REPUBLIC OF CHINA
[email protected]
DRAFT. Not for citation or distribution
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Abstract
North Korea is arguably the most heavily sanctioned country in the world. While sanctions
have largely failed to achieve political successes in North Korea, because it is also one of the
most politically isolated and data-poor countries in the world, it is unclear what economic
effect sanctions have had on the country. In this paper, we use analysis of a unique dataset of
daily food commodity prices in Pyongyang official and black markets from 2010 to 2015 to
measure the impact of sanctions on North Korea food prices. Using time series econometric
models, we find evidence that the North Korean economy suffers from UN sanctions, but
may use food prices to cushion the blow, but is unable to cushion the blow entirely. Sanctions
have a positive effect on imported food prices, and a negative effect on some domestically
produced food, suggesting that the North Korean state suffers the effects of sanctions, but
compensates through substituting domestic goods. Our study has implications not only for
the study of North Korea, and for the literature on the political economy of sanctions.
Keywords
Food prices, commodity prices, North Korea, economic sanctions, sanction effects
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Acknowledgments: Thanks to Katja Kleinberg and panel participants at the 2016
International Studies Association annual meeting in Atlanta, GA, as well as the participants at
the University of Sydney’s Department of Government and International Relations Security
Studies Scholars Seminar, where this paper was presented. Haneol Lee provided research
assistance. This work was supported by the Australian Research Council (grant
DP140102098) and the University of Sydney.
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INTRODUCTION
What effect have sanctions had on North Korea? North Korea (formally the
Democratic People’s Republic of Korea) is perhaps the most comprehensively sanctioned
country in history. This is largely due to North Korea’s extended tit-for-tat with the
international community over its nuclear weapons and missile development programs,
stretching back to 1993, with the onset of the first Korean nuclear crisis, and picking up in
earnest with its 2006 missile and nuclear tests, which were followed by several rounds of
sanctions. Since then North Korea has conducted four more nuclear tests, and a plethora of
missile tests, all of which were eventually followed by UN sanctions. North Korea detonated
what it called a 'hydrogen bomb' in January 2016, with the resultant sanctions being issued in
March of that year.
North Korea is far from the only country under sanctions, as sanctions have become
more popular as a tool of statecraft short of war to coerce other states (Giumelli, 2015).
Studies of sanctions’ effects have traditionally been concerned with whether they are
successful in attaining their political goals, both in general, and in specific cases (Chan and
Drury, 2000, Miller, 2014, Elliott, 1998, Ronzitti, 2016, Drezner, 2011, Pape, 1997, Ashford,
2016, Eckert and Biersteker, 2012, Rosenberg et al., 2015), not with whether they have an
economic effect on the targeted country. Here, the evidence is ambiguous: sanctions with
limited goals attain their objectives about half the time, and sanctions with major goals
(whether regime change, or military impairment) succeed 30% of the time (Hufbauer et al.,
2007). In general, limited sanctions appear to be more likely to achieve political goals (Eckert
and Biersteker, 2012). It is difficult to generalize about the efficacy of sanctions, particularly
given the wide variety of sanctions that have been developed in the past several decades.
While repeated rounds of sanctions aimed at North Korea have been effective in expressing
the sense of the international community that North Korea’s behavior is unacceptable, and in
enforcing the norm of non-proliferation, clearly they have not coerced the North Korea into
giving up its nuclear weapons or missiles, let alone brought it back to the negotiating table
(Park and Walsh, 2016): 9.
This paper will sidestep whether sanctions against North Korea (or anywhere else) are
'effective' in achieving their stated goals. Rather, we are interested in the intermediate step: to
what extent sanctions, once adopted, actually have an impact on the economy of the target
country. The traditional pathway for sanctions to coerce a target country to engage in a given
behavior is to cause (or threaten to cause) economic damage in the target country, either by
weakening or curtailing the resources of the central government, or by harming the wellbeing of the core elite supporters of the government (Hufbauer et al., 2007, Kaempfer and
Lowenberg, 1988). If the sanctions are sufficiently painful (or are likely to be painful), the
central government may change its policies on its own to stop the hurting, elite supporters
may overthrow the government, or political power within the government and its elite
supporters may shift in favor of acquiescing to the sanctioning countries’ demands (Kirshner,
1997)
Assuming that a given set of sanctions are intended to cause economic damage, the
first step, then, is to determine whether sanctions have any economic effect on the sanctioned
countries. Here the evidence is ambiguous. Some studies have found that economic sanctions
do not succeed in damaging economic conditions in targeted countries (Shin et al., 2015), that
many countries may actively bust sanctions, thus minimizing economic effects (Early, 2015),
and that UN sanctions do not have a negative effect on foreign aid flows to targeted countries
(and that US sanctions actually increase other donors’ aid) (Early and Jadoon, 2015). Others
have concluded the sanctions can drag down GDP (Neuenkirch and Neumeier, 2014), and
private investment in targeted countries (Rosenberg et al., 2015), harm innocents and burden
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firms that are uninvolved in the political spats (Kaempfer and Lowenberg, 2007), damage
public health (conditional on a large economic effect) (Allen and Lektzian, 2013), and
contribute to financial instability within the country (Peksen and Son, 2015).
In the case of North Korea, one of the most politically isolated countries in the world,
measuring the effects of sanctions on North Korea’s economy is complicated by the near total
lack of information. While interviews with defectors and Chinese businessmen (Hastings,
2016) have been useful in determining the pathways by which North Koreans (and more
specifically North Korean state trading companies) have adapted to sanctions (Park and
Walsh, 2016, Park, 2009, Park, Fall 2014), these reports have generally focused on effect in
terms of whether sanctions have made it more difficult for North Korea to procure materials
for its development weapons of mass destruction, and whether they have made it more
difficult for North Korea to raise hard currency through illicit trade (Greitens, 2014)
Quantitative data to measure the welfare effects on North Korean citizens is more
difficult to come by. The North Korean government stopped releasing general economic data
in the mid-1960s, and what little is released now in statistical yearbooks is almost certainly
manipulated or incomplete. As a result, even basic data such as gross domestic product
figures are actually estimates by other countries (notably South Korea) based on oftenproprietary information. The World Food Program occasionally releases reports assessing
North Korea’s food situation with yearly estimates of production in various commodities
(although, except for rice, none under study in this article), with most of the information
coming from North Korean official records (Gunjal et al., 28 November 2013).
We suggest that one way to measure the effects of sanctions on North Korea is to look
at food prices in Pyongyang using a unique dataset consisting of the daily prices of food
commodities sold in Pyongyang markets between January 2010 and May 2015. Food prices
are perhaps one of the best indicators for the welfare (or lack thereof) of a country’s
inhabitants, and food shocks are connected to regime instability and conflict in developing
countries (Hendrix and Haggard, 2015, Hendrix and Brinkman, 2013, Arezki and Bruckner,
2011).
This time period is a particularly opportune time in North Korea’s history to study the
effect of sanctions. In November 2009, the state made a surprise push to revalue the North
Korean won by replacing the old won notes with new won with a face value of 1/100 of the
old currency. It gave the population one week to replace their notes, closed markets for an
indefinite period, and limited the amount they could replace to approximately US$30,
effectively wiping out any savings in old won (Haggard and Noland, 2010b). The markets
reopened in February 2010, essentially starting North Korea over in terms of price
stabilization and market development. There was also an extended period of crisis between
North Korea and the rest of the world, accompanied by two rounds of increasingly punitive
sanctions.
In December 2012, North Korea launched a missile, apparently into orbit, in violation
of United Nations Security Council resolutions. The UN Security Council responded with
sanctions the next month, which set off a range of North Korean provocations, including a
third nuclear test (which in turn sparked more sanctions in March 2013 and a temporary
Chinese crackdown on North Korean trade), mobilization of military forces, threats against
other countries, more weapons tests, and the closure of the Kaesong Industrial Complex,
which lasted until September 2013. Finally, North Korea was also convulsed by political
instability in the form of leadership change. In December 2011, Kim Jong-il died, and was
replaced by his son Kim Jong-un, who spent the next several consolidating his power, with
this most dramatically demonstrated by the purge and execution of his uncle Jang Song-thaek
in December 2013.
This paper makes several important contributions. First, it brings to bear a unique
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dataset to better understand the political economy of one of the most opaque countries in the
world. As such, it contributes to the growing literature that looks at the economic effects of
sanctions around the world. While this is not the first piece to study the connections between
North Korea’s political economy and sanctions or trade (Eberstadt, 4 June 2014, Haggard and
Noland, 2010a, Frank, 2006, Haggard and Noland, 2012), it is the first study to look at the
short-term effect of sanctions in North Korea using quantitative methods on such granular
data. In general, literature on the economic effects of sanctions looks at country-level yearon-year effects, while in this paper, we can measure the effects down to the day in the most
important city in North Korea. Finally, we contribute to the literature on sanctions by making
the first tentative steps in positing a mechanism by which the North Korean state or markets
may be addressing its supporters’ welfare during sanctions and crises.
The rest of the paper proceeds as follows. First, we propose a way to understand the
relationship between sanctions and commodity prices. The North Korean regime is likely to
suffer the effects of sanctions in terms of the price increases for imported food, but may
attempt to blunt that effect with local food price moderation. Second, we discuss the data and
the variables used. Third, we discuss the empirical strategy used. Finally, we discuss the
results. We find that United Nations sanctions increase prices on food that North Korea must
import, and decrease prices on at least some food that can be acquired domestically. In
additional findings, Chinese government crackdowns on North Korean trade and the 2013
Korean Peninsula Crisis are associated with changes in price levels as well, with Chinese
smuggling crackdowns decreasing imported food prices, and the 2013 crisis increasing
cabbage prices, indicating that China may be busting sanctions for North Korea, but also that
crises do negatively affect North Korean welfare.
THE EFFECTS OF SANCTIONS
Regimes that are the targets of sanctions may react in a number of ways (aside from
acquiescing) to protect themselves. Economic sanctions may cause targeted regimes to
become more repressive (Peksen and Drury, 2010, Wood, 2008, Escribà‐Folch and Wright,
2010), but the North Korean regime is already arguably the most repressive in the world.
Regimes may also manipulate potential opposition who are harmed by sanctions to create
monopolies to both blunt the force of sanctions economically and solidify their power (Rowe,
2001). Targeted states may also seek to cushion the economic blow from sanctions on their
populations. For example, they may attempt to replace food (or other items) that is no longer
imported with domestic substitutes (Wegren, 2014). The nature of the regime may affect how
targeted states respond to sanctions. Given that all regimes are dependent on a core of elite
supporters, authoritarian regimes may act to reduce the pain their supporters feel (Kaempfer
and Lowenberg, 2007). Single-party states may seek to transfer resources to their key
constituencies, while military regimes spend money on military goods and services (their
primary constituency), and personalistic regimes reduce spending and increase repression
everywhere (Escribà-Folch, 2012).
Kim Jong-un is clearly at the center of the North Korean state in a manner that would
characterize personalistic regimes, but North Korea might better be seen as a single-party
state. While Kim maintains a cult of personality, he is dependent for political survival on the
support of a selectorate (De Mesquita et al., 2002, De Mesquita and Smith, 2010), in this case,
Workers’ Party, military, and government elites, physically centered in Pyongyang (Collins,
2016, Byman and Lind, 2010). Kim maintains the support of these elites through a
combination of access to the Public Distribution System (PDS) (for the core elite),
distribution of luxury goods, availability of goods in markets, and opportunities for making
money through state enterprises and semi-private businesses (Byman and Lind, 2010;
Hastings, 2016). Living in Pyongyang itself is to a certain extent a marker for elite status
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(although there continues to be food insecurity even within Pyongyang (Gunjal et al., 28
November 2013), and the visible development that has marked Pyongyang’s landscape since
Kim Jong-un’s ascension could itself be seen as an indicator of co-optation (Collins 2016). In
this sense, Pyongyang serves as a critical case: the effects sanctions have on Pyongyang (and
particularly on the wallets and stomachs of Pyongyang residents) can tell us much not only
about how the economy of North Korea functions, but also on the domestic political import
of what happens to North Korea externally. North Korea can attempt to cushion the blow
from sanctions, but can do so most effectively when the goods themselves are not subject to
constraints due to trade restrictions. The central intuition of this paper is that North Korea
suffers from impediments to trade, with resulting positive effects on price levels imported
goods, but attempts to cushion these effects through negative changes in the prices of
domestic goods.
Particularly given that hostile actions against North Korea have been almost entirely
reactive since 2006 (with North Korea engaging in a provocation, and other states imposing
sanctions), sanctions are likely to be endogenous to conditions on the ground; that is, the
North Korean central state has a choice about when to engage in crises. The 2013 crisis, for
instance, was precipitated by North Korea’s 13 December 2012 launch of a long-range
missile that ostensibly put a satellite into space. The UN responded by imposing new
sanctions on 22 January 2013, with a third North Korean nuclear test following on 12
February, and the effective closure of Kaesong SEZ on 9 April (when the North Korean
workers did not report to work). Tensions finally began cooling with North Korea’s proposal
of talks with South Korea on 6 June, and the eventual reopening of Kaesong on 16 September.
North Korea may time crises to test the reactions of South Korean (and to a lesser extent
Chinese and US) leaders, particularly new leaders such as (in 2013) South Korean President
Park Geun-hye. North Korea may also instigate crises as a means of sending signals to other
countries of its displeasure, signals that for other countries with a functioning diplomatic
corps would be done through diplomatic channels (Kelly, 1 April 2014).
The paradox for the North Korean state is that, assuming that miscalculations do not
lead to outright war, the international turmoil caused by North Korean crises is useful as a
means of improving domestic political stability: through instigating crises, Kim Jong-un (and
Kim Jong-il before him) can appear to be standing up to outside, hostile forces, for the
benefit of the population, and can cultivate a ‘barracks state’, in which a permanent sense of
crisis justifies the state’s restrictions on and mobilization of the civilian population. Kim can
also use crises to play to factions (primarily the military) within the North Korean state who
want confrontation with the United States, Japan, and South Korea, and more generally to
justify large military budgets and develop (and practice) North Korea’s military capabilities
(Kelly 2014).
Nonetheless, while North Korea chooses when and how to instigate crises, and may
benefit domestically from the turmoil abroad, this does not mean there is no cost: the
imposition of sanctions and the general downturns in trade that accompanies crises has the
potential to harm access to consumer goods and food. If food supply is sufficiently
constricted during crises, this could cause problems for domestic political stability, and at the
very least would negate the political benefits that North Korean regime would enjoy by
instigating the crisis in the first place.
As such, the regime has an especially strong incentive to maintain price levels in
Pyongyang itself, even if the rest of the country is suffering from food shortages. This is
complicated for the regime in that, while prices in the official markets are theoretically set by
the state, in practice the prices appear to either be ignored or the official prices actually are a
reflection of the market prices (Lee, 16 November 2015). While North Korea is generally
thought by casual observers as a socialist command economy, in fact a substantial subset of
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the economy is at least partially market-driven, to the point that many scholars speak of
North Korea as having multiple economies, with the formal, state-owned economy only one
subset, along with the economy designed to provide goods and money to the Kim regime and
elites (particularly in Pyongyang), the military economy, and the private, often black market
economy that provides for the majority of the population (Habib, 2011, Chung, 2012, Kim,
2013). While food is theoretically provided to all North Koreans through the Public
Distribution System, in practice the PDS broke down at the end of the Cold War, and has
failed to provide a stable source of food to anyone but certain elites and military personnel
since the early 1990s (Haggard and Noland 2005).
Instead, North Koreans obtain food from their own farming in excess of the official
quotas, from the informal markets (jangmadang) that have sprung up throughout the country
since the end of the Cold War, and through official farmers’ (now general) markets (Haggard
and Noland, 2007, Lankov et al., 2013, Lankov and Kim, Spring 2008, Haggard and Noland,
2005, Silberstein, 2015, Tudor and Pearson, 2015, Smith, 2015). These formal markets are
usually divided into several smaller zones, with each selling a specific category of goods
(Yang, 2009). However, the farmers’ markets do not merely provide consumers with
agricultural products (foodstuffs collected from foreign importation as well as North Korean
farmers, PDS, and military diversion), but also sell a great variety of non-food items
including electronic goods, clothes, and stationery as well as cheap plastic household items
(Everard 2011; Yang 2009). The second kind of market in North Korea is the informal
private black market, which is not recognized by the government, but is de facto allowed to
exist. Unlike the officially regulated farmers markets, price boards are not on display in
North Korean black markets, but vendors do often indicate the prices of their goods on scraps
of brown paper stuck onto their baskets. In contrast to farmers’ markets, black markets sell
mostly inexpensive but high-quality raw and cooked food. In general, products sold in these
black markets are mainly those that are officially forbidden from being sold in formal
markets (Everard, 2011).
Since the farmers’ markets and black markets from which the data for this article
were drawn do not in fact have prices set by the state, it is possible that the state manipulates
prices in Pyongyang by (1) transferring food from warehouses or other parts of the country to
Pyongyang and indirectly releasing them into the markets (black markets and farmers’
markets alike), or by (2) allowing more smuggling (or simply importation) of commodities
from China to compensate. Given the prowess of North Korea’s trade networks in importing
sanctioned goods against the will of the international community, non-sanctioned goods such
as food should be easier to acquire (Hastings, 2016). Sellers themselves may also attempt to
compensate for shocks by increasing the supply of food types to which they have access (that
is, domestically produced foods). The provision of economic stability during periods of
political instability can be tested both over Kim Jong-un's entire rule, and during the 2013
crisis specifically, two ‘shocks’ that are entirely internally driven.
Implementation is at the center of the debate about North Korea and sanctions
(Experts, 6 March 2014, Eckert and Biersteker, 2012, Wertz and Vaez, 2012). North Korea’s
main (and arguably only) ally, China, plays a complex role in enforcing sanctions, and thus in
measuring the effects of sanctions on North Korea. For its own strategic reasons, China has
tempered other countries’ strict sanctions with a long-term bilateral economic relationship
that includes outright aid (Reilly, 2014c), the heavy involvement of private firms (at the
instigation of the Chinese government) with a focus on market-rational trade and investment
decisions (Yoon and Lee, 2013, Reilly, 2014b), construction of infrastructure between China
and North Korea and within North Korea to encourage trade and development, and
encouragement of Chinese-style market reforms through expert exchanges, seminars, trade
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shows, and bilateral discussions (Reilly, 2014b, Reilly, 2014a). As a result, North KoreaChina bilateral trade has skyrocketed since 2006 (Eberstadt, 4 June 2014).
While China has been unwilling to allow North Korea to collapse, and has often run
political interference for North Korea (such as during the ROKS Cheonan investigation)
(Beauchamp-Mustafaga and Jun, 2013), it is occasionally willing to signal its displeasure
with North Korea’s provocations by temporarily increasing customs enforcement (Blanchard,
30 April 2013), hindering trade with North Korea (particularly the provision of oil) (Jeffries,
2013): 418, and voting for (or at least not vetoing) sanctions in the United Nations Security
Council. As a result, we would expect that when China chooses to send a signal to North
Korea, this signal is likely to come in the form of sanctions enforcement and trade
crackdowns sufficient to have ripple effects in Pyongyang itself. We would expect United
Nations sanctions to have similar effects on Pyongyang prices, as sanctions, while not
directly targeting food, may make it more difficult to import any goods into North Korea
(given that sanctions enforcement is usually characterized by lengthy inspections and wait
times at border checkpoints), resulting in increased price levels for imported foods. This leads
to the following hypothesis:
Hypothesis 1. Increasing sanctions are associated with increased price levels in
imported foods.
The effect of sanctions on domestically produced foods is necessarily less direct, since the
foods are not being imported (let alone being sanctioned). The North Korean regime may
respond by increasing the supply of domestically produced goods to compensate, resulting in
a decrease in the price levels of domestically produced foods even as sanction increase. This
could also be accomplished through traders and farmers operating independently, inasmuch
as sanctions and trade holdups may cause them to release more domestically produced foods
into the markets (and in the long run, to substitute domestically produced and consumed food
for other goods produced).
Hypothesis 2. Increasing sanctions are associated with decreased price levels in
domestically produced foods.
DATA
Dependent variables
In general, although the United Nations World Food Program produces relatively
regular reports with data,1 North Korea has terrible (or simply incorrect) data, making it
difficult to understand the country’s political and economic situation with clarity, particularly
on a daily basis. As a result, we resorted to data collected not by the North Korean
government, but by foreigners invested in North Korea. Table 1 shows the descriptive
statistics for the variables used.
The dependent variables consist of prices (in North Korean won) collected daily on
four different commodities in from 1 January 2010 until 17 May 2015.2 While the prices are
daily, they were aggregated to weekly averages to smooth potentially distortionary daily
fluctuations. We focused on eight commodities – rice, pork, Walleye Pollock, cabbage – that
might track closely with fortunes in Pyongyang. The data points themselves were sourced
from a group of Chinese investors for the period from 1 January 2010 to 31 December 2012
and from 5 July 2014 through 17 May 2015, and from a second group of Chinese investors in
Pyongyang from 1 January 2012 to 4 July 2014, giving a maximum of 1963 daily prices for
each commodity (although in practice there were some commodities with fewer data points
either due to lack of data collection or because they were not sold in markets on that
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particular day). Time series of each commodity price combined with precipitation levels can
be seen in Figure 1.
The commodity prices were mostly collected from Tongil market, the largest official
market in Pyongyang, and a number of black markets. Due to poor refrigeration, investors
must purchase commodities frequently, both for their catering businesses, and to feed their
employees. For the first and third periods in the data, the prices are averages of prices
collected from multiple markets (although in practice most of the prices came from Tongil
market). Rice and pork are both imported into North Korea on a regular basis, and Walleye
Pollock and cabbage are both produced domestically.
In North Korea, rice is strictly forbidden from being sold in official markets because
the North Korean government considers it to be a strategic asset that must only be distributed
through the PDS. As a result, prices used here were sourced from black markets in
Pyongyang. When former British ambassador to North Korea John Everard observed
Pyongyang markets, he never saw rice for sale inside an official Pyongyang market, but did
see it in black markets, sometimes out of sacks clearly marked “Public of Korea” or “World
Food Program.” (Everard 2011) Pork prices were mainly collected from Tongil market, and
Taesong market, a market known its high-quality imported pork.
Among domestically produced food, Walleye Pollock in the dataset was purchased
from Pyongyang’s Raewon market, which is known for its seafood, and black markets, and
consists of only fully processed dried fish instead of fresh fish, due to the inability of North
Korean infrastructure to refrigerate food. Pollock is likely domestically caught and processed,
since seafood is one of the few food exports of the DPRK. Cabbage is the most important
vegetable in North Korean people’s everyday life. It is one of the few agricultural products
which does not rely on imports, and can be purchased from any farmer’s market in
Pyongyang with no purchase and sale limits. Cabbage prices provided by this list cover a
large range of different markets in Pyongyang in which the prices of this vegetable are
essentially the same.
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Panel a: Rice Price and Precipitation
Panel b: Pork Price and Precipitation
Panel c: Pollock Price and Precipitation
Panel d: Cabbage Price and Precipitation
Figure 1: Commodity prices and weekly precipitation
Sanctions
Sanctions are coded as an ordinal variable with increasing value as additional
sanctions are imposed. The UN sanctions that begin the time period under study remained
unchanged until 22 January 2013, when, after North Korea’s launch of a satellite using a
ballistic missile, the Security Council passed resolution 2087, which did little but add some
individuals, institutions, and items to the sanctions list (Council, 22 January 2013). Following
North Korea’s third nuclear test on 12 February, the Security Council passed resolution 2094.
This resolution had more teeth: in addition to adding even more institutions and individuals
to the sanctions list, and banning intermediate services related to banned trade, financial
sanctions were expanded to bulk cash transfers and made mandatory for members states.
Luxury goods were more clearly defined, and states were called upon to stop the opening up
of any new North Korean financial accounts, and to ban their own banks from doing business
with North Korea (although existing accounts were not required to be closed, likely at the
behest of China). States were supposed to inspect vessels, craft, and vehicles for North
Korean-related banned goods, and to bar North Korean ships from port if they declined to be
inspected (Council, 7 March 2013).
While the sanctions passed in 2013 explicitly did not cover food imports (in fact, food,
with the exception of luxury items such as certain brands of spirits, has never been
sanctioned), we can imagine mechanisms by which an expansion of sanctions (or rather,
increased enforcement of sanctions) might affect food prices. First, China and other countries
might inspect all shipments to North Korea more closely, slowing down and limiting the
import of all goods, including food. Second, the companies and individuals that import food
might be hindered in some way because the sanctions, either because they are on the
sanctions list themselves, because countries wary of violating sanctions might decline with
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any North Korean businesses at all, or because the means by which food is imported into
North Korea, North Korean ships and trucks, and the means by which purchases are financed,
through North Korean banks, are themselves subject to increased ostracism, inspections, and
bans, making it more difficult for importers to operate.
Control variables
Impositions of sanctions in general are external to North Korea, but are triggered by
North Korean behavior, and are anticipated by the North Korean state. As such, we need to
deal with potential validity concerns: it may not be just the sanctions causing shifts in price
levels, but the actions of North Korea that are causing the sanctions and the price shifts.
North Korea may also be adjusting price levels in anticipation of sanctions (which it knows
are coming due its provocative behavior).
We address this by including a variable for the 2013 Korean Peninsula Crisis, during
which both of the 2013 UN sanctions resolutions were passed. North Korea precipitated the
crisis by a December 2012 missile test, followed by the United Nations’ response to the test
in January 2013, and North Korea’s third nuclear test in February 2013 (with the UN’s
response in March 2013 expected but external to North Korea). As such, in the analysis, we
include two variables for the 2013 crisis, one in which the crisis begins with North Korea’s
missile test (clearly internally driven), and one in which the crisis begins with UN sanctions
(the timing of which was externally driven although likely anticipated by North Korea). Both
crisis variables end with the reopening of Kaesong Industrial Complex in September 2013.
We also include variables for Chinese crackdowns on North Korean trade during the
2013 crisis, thus taking into account other factors that may affect North Korean food prices
which are anticipated by North Korea but for which North Korea controls neither the timing
nor the nature. Chinese crackdowns include Chinese government enforcement of pre-existing
United Nations sanctions (which included rigorous inspection of North Korean cargo as a
means of delaying the cargo and pressuring of North Korean elites) (Charbonneau and
Nichols, 5 March 2013), a crackdown on illicit smuggling into and out of North Korea, and a
crackdown on North Korean banks operating in China (Bradsher and Cumming-Bruce, 7
May 2013).
These are surprisingly difficult to account for. The Chinese government often does
not announce when it is enforcing sanctions or cracking down on North Korean imports and
exports, preferring instead to have the ability to send discreet signals to North Korea about its
anger over North Korea’s provocations through cutting off oil supplies, or simply starting to
inspect goods entering and leaving North Korea more closely (although it was more blatant
about sanctions enforcement at the outset of 2016 round of sanctions (Tiezzi, 10 March
2016)). This leaves us either to get the data from alternative sources or to guess. Moreover,
even when crackdowns are announced, the end of those crackdowns never is, for obvious
reasons: it signals to North Korea and the rest of the world that China is no longer serious
about enforcing sanctions. As a result, we assume that China’s crackdowns in 2013 ended
with the joint North Korea-China proposal for a return to the Six Party talks on 19 June
(CNN, 19 June 2013), which can be taken as a sign that North Korea was willing to ratchet
down tension to the satisfaction of China.
The control variables also include the natural logarithm of Won per US Dollars
exchange rates to take into account the value of the North Korean won; the four-week
running sum of precipitation levels; the seasonal dummy variable for lean periods (when
North Korea’s previous year’s harvest has run low, but the next harvest has not yet come
available), and the data-source dummy variable to account for potential discrepancies in the
different data sources. The precipitation data for Pyongyang for the relevant time period
come from the South Korean government’s meteorological agency. The North Korean
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won/US dollar exchange rate is the Pyongyang black market exchange reported (with
estimated interpolated prices for the time periods that lack data) by DailyNK.3
Internal political shocks within North Korea during the time period under study
include the death of Kim Jong-il and shift to Kim Jong-un as supreme leader of North Korea
in December 2011, and the purge of Jang Song-thaek in December 2013. The rise of Kim
Jong-un and the purge of Jang Song-thaek are especially useful since they represent fairly
significant, known shifts in the elite power structure of North Korea, and as such may be
relevant to commodity prices, inasmuch as political uncertainty could lead to uncertainty
among the population about the availability and price of different food items.
Table 1: Descriptive statistics
Variable
Rice
Pollock
Cabbage
UN Sanctions
China Enforcement
Jang Song-thaek Purge
2013 Crisis
China Smuggling
Crackdown
China Banking
Crackdown
Pyongyang Precipitation
(mm)
Won per USD
Kim Jong-un in Power
Pork (Corrected)
2013 Crisis (Missile)
Obs
1962
1945
1960
1963
1963
1963
1963
1963
Mean
3505.79
12756.96
2347.37
0.42
0.07
0.27
0.12
0.05
Std. Dev.
1924.57
3224.61
978.63
0.49
0.26
0.44
0.33
0.22
Min
200
2500
70
0
0
0
0
0
Max
7400
20200
4250
1
1
1
1
1
1963
0.04
0.20
0
1
1963
4.20
16.81
0
289
589
1963
1961
1963
4241.42
0.64
1713.50
0.14
2936.27
0.48
1026.54
0.35
120
0
120
0
9100
1
4000
1
EMPIRICAL STRATEGY
Analysis involves weekly data, calculated from daily observations. Missing values in
daily series are interpolated using a simple linear method. In the case of several commodities,
there were apparent shifts in price levels due to changes in data sources (see Appendix). In
such instances the prices were adjusted to facilitate continuity of time series. Weekly prices
then are obtained by simple averaging. Original prices are quoted in North Korean won. To
facilitate the better interpretation of the results, as well as mitigate the high levels of volatility
in the series in the beginning of the sample period, we transform prices to natural logarithms.
As such, parameter estimates, unless otherwise stated, will represent elasticities, and should
be interpreted as relative changes of prices with respect to a unit change in explanatory
variable of interest. From here forward, yit will denote the log-price of a commodity i in
period t.
Initial analysis
We begin by examining the dynamic properties of the considered log-prices. The null
hypotheses of nonstationarity are assessed in an augmented Dickey-Fuller (ADF) unit root
testing framework. The results of this testing procedure are presented in Table 2.
Table 2: Augmented Dickey-Fuller unit root test results
!
13!
ADF Test
Levels
First-Differences
Rice
-3.08
-9.00
Pork
-3.02
-6.60
Pollock
-6.46
-6.77
Cabbage
-3.91
-11.42
Note: The 1% and 5% critical values of the null hypothesis of random
walk with drift are -3.46 and -2.88, respectively.
In the case of the prices of pollock and cabbage, the null is rejected at the
conventional level of statistical significance, suggesting that the price series are possibly
weakly dependent. Nonetheless, the prices still appear (and, to some extent, are expected) to
be characterized by a persistent behavior. As such, we err on the safe side, and proceed by
working with the first-differenced series, but incorporate the lagged dependent variable in the
right-hand-side of the equation, i.e., maintain the ADF structure:
Δ𝑦𝑡=𝛼+𝛽𝑦𝑡−1+𝑖=1𝑝−1𝛾𝑖Δ𝑦𝑡−𝑖+𝛅′𝐱t+𝜽′𝒛𝑡+𝜀𝑡,
(1)
where the commodity-specific subscript is dropped for the sake of illustration; Δ is the firstdifference operator; 𝑦𝑡 is the natural logarithm of price series; 𝐱t is a vector of policy
variables and shocks, and 𝒛𝑡 is a vector of controls (potential price shifters); further,
𝜀𝑡∼𝑖𝑖𝑑(0,𝜎2); and the rest are parameters to be estimated.
Estimation and sensitivity analysis
The external and internal shocks and sanctions are illustrated in Figure 2, while
natural logarithms of commodity prices, along with the weekly rainfall data, are plotted in
Figure 3. Several features of interest emerge from these figures. First, the majority of prices
tend to be trending upwards initially, but level off afterwards (the price stabilization
coincides with Kim Jong-un coming to power). This is particularly true for rice and pork, as
also seen in Figure 1. In addition, on one hand the post-2011 sanctions, and on the other hand
external shocks of 2013, greatly overlap, so care is needed in the estimation stage to avoid the
multicollinearity and identification issues. Also notably, even with log-prices there seems to
be a high degree of (relative) price volatility during the first half of 2010 – a period that is not
associated with particular sanctions or shocks (but is associated with the North Korean
economy recovering from the disastrous currency reform in November 2009). While some of
this excessive variability can be explained by volatile exchange rates in the coinciding period
– a factor that we control for in the analysis – these observations may also be treated as
“outliers,” at least in the context of the current exercise. In this analysis we thus chose a
simple approach of excluding first 26 weeks of data (the estimation results were qualitatively
similar when we excluded first 52 weeks of data).
!
14!
Figure 2. Shifters and controls
Figure 3. Commodity prices and precipitation
A number of candidate models are estimated to facilitate identification of the effects
of sanctions, and to provide robustness checks. All models include the rainfall variable, the
dummy variable for the lean season, and the dummy variable to control for the source of data.
In addition, the price level models include the exchange rates and the autoregressive variables.
In particular, across the equations, the AR(2) specification is maintained, which eliminates
much of any residual autocorrelation in the regressions. Moreover, all models except for the
baseline specifications include dummy variables indicating Kim Jong-un being in power, and
Jang Song-thaek's purge. All models except for the baseline specifications include UN
sanctions as the primary independent variable of interest.
Alternative specifications
!
15!
We include baseline specifications for UN sanctions, and both specifications of the
2013 crisis, as well as US and European sanctions (Models A.1-A.5 in Tables A.1-A.4). The
United States and the European Union passed their own sets of sanctions against North Korea
during the time period under study, although these were mostly financial sanctions and
moves to add additional individuals and institutions to sanctions lists. It is difficult to parse
out the separate effect that US and EU sanctions may have had on North Korea, since the
sanctions were often implemented in response to and in concert with UN sanctions. The US,
for instance, passed new sanctions on April 18, 2011 and May 23, 2011, and then four sets
during the 2013 Crisis (January 24, March 7, March 11, and June 27), while the EU
implemented a set of sanctions on December 21, 2011, then passed four sets of sanctions
itself during the 2013 Crisis (February 18, March 26, April 23, and July 22).4
We also include model specifications for UN sanctions that take into account the
different definitions of the 2013 crisis, as well as different specifications for Chinese
government crackdowns (notably Chinese enforcement as a whole, and the banking
crackdown), with and without the 2013 crisis variables (Models B.1-B.12 in Tables A.1-A.4).
The results are ambiguous: with alternative specifications, the UN sanctions variable
sometimes drops out of significance. However, the sign for the variable is consistent across
models for each commodity.
RESULTS AND DISCUSSION
The estimation results of interest, which include the UN sanctions, as well as the 2013
crisis and China’s primary crackdown (on smuggling) during the Crisis, are given in Table 3.
All results, including alternative specifications, are reported in Tables A.1-A.4. All nonbaseline models incorporate UN sanctions. The tables consist of one panel for each
commodity. Across all panels, the tables present short-run price semi-elasticities (with
standard errors).
Table 3. Models by commodity
Independent
variables
UN Sanctions
Kim Jong-un in
power
Jang Song-thaek
purged
2013 Crisis
(sanctions)
Smuggling
crackdown
Rice
Pork
Pollock
Cabbage
0.017* (0.009)
-0.004 (0.019)
0.015* (0.009)
-0.007 (0.016)
-0.004 (0.004)
-0.004 (0.007)
-0.019** (0.009)
0.024 (0.019)
-0.022 (0.019)
-0.036** (0.018)
0.003 (0.008)
0.030 (0.020)
0.011 (0.020)
0.017 (0.017)
0.009 (0.008)
0.037* (0.019)
-0.088*** (0.024)
-0.042** (0.021)
-0.004 (0.010)
-0.015 (0.023)
* = p<.1; ** = p<.05; *** = p<0.01. Control variables and lags are not reported.
While North Korea often blames food shortages on adverse weather – specifically
heavy rains and floods (usually in June through September) that wash away crops, inundate
fields, flood power generation facilities, and cut off roads and rails (resulting in an inability to
move coal from the mines to the power plants to generate electricity) – when controlling for
other factors, neither precipitation nor so-called lean seasons have a significant effect on food
prices in Pyongyang. This suggests either that bad weather is not a cause of North Korea's
food shortages (at least for the time period under consideration), or that the North Korean
state cushions the food shortages during the lean seasons and after floods or droughts to
prevent Pyongyang from suffering too much, suggesting the disconnect between elites and
the general population. With that said, sharp spikes in prices in Pyongyang due to weather
!
16!
problems are not unheard of: in August 2013, the price of rice in Pyongyang reportedly
spiked because shortages elsewhere caused the state to divert rice from Pyongyang to other
parts of the country.5
Escalating United Nations sanctions have indeed had an effect on imported food
prices. Imported commodity price levels operate in accordance with Hypothesis 1: pork and
rice both increase in price in response to sanctions. This suggests that UN sanctions do in fact
make it (marginally) more difficult for North Korea to acquire imported commodities, and
domestically produced commodities may be released or shifted to markets to compensate.
They may also be an indirect indicator of unobserved Chinese crackdowns. China’s
acquiescence to additional United Nations sanctions in a given instance is unusual enough
that, even in the absence of a publicly announced Chinese crackdown, there may be changes
behind the scenes that make it more difficult for North Korea to engage in certain kinds of
trade in the weeks and months after a sanctions resolution is passed. As a result, while it is
important to look at any announced or reported crackdowns on North Korean trade, there are
likely to be unobserved crackdowns as well, and the passage of new sanctions resolutions
may be associated with a crackdown, even if one is not announced.
Since they occurred at approximately the same time, it is difficult to parse out the
differing effects of the 2013 crisis and China's enforcement actions. The smuggling
crackdown, considered with and without either specification of the 2013 crisis, is associated
with decreased price levels in rice and pork.6 There are several explanations for this. First,
China itself may be compensating for the crackdowns on illicit trade by allowing the
importation of more rice and pork (or more generally, food) into North Korea through legal
channels, even as it cracks down on other goods and otherwise holds up trade. Second, North
Korea may be releasing rice and pork from stockpiles into Pyongyang black markets or to the
PDS (which would decrease demand for rice in the black markets) directly in response to
Chinese government crackdowns (and not the crisis that precipitated the crackdown).
Whatever its public show of force, China did not actually crack down hard on trade during
the period in which its crackdowns were supposedly occurring in 2013 (Bradsher and
Cumming-Bruce, 7 May 2013), a sentiment echoed by North Korean traders in 2016 when
contemplating the potential for the 2016 round of sanctions to impede trade (Seol, 7 March
2016). China thus effectively became a sanctions buster (Early, 2015, Early, 2011, Early and
Jadoon, 2015, Haggard and Noland, 2010a).
As for domestically produced food, the results are ambiguous. Walleye Pollock shows
no statistically significant association with UN sanctions (or any independent variables),
although the coefficients are in the expected direction. While Pollock is produced
domestically, given its high cost per kilogram, it may be the case that Pollock is only lightly
traded, and is bought primarily by a small number of North Korean elites (and resident
foreigners) who are significantly wealthier even than the average North Korean Pyongyang
resident. As a result, Pollock may not be particularly sensitive to shocks (and the data suggest
that the price is not especially variable in general). More generally, we would expect the
effects of sanctions to be smaller on price levels for domestically produced goods, since there
is no direct causal connection between the two.
Cabbage does show statistically significant results, with price levels decreasing in
response to UN sanctions across all models where the 2013 crisis (as defined by the January
2013 UN sanctions) is included. For cabbage, the 2013 crisis itself increases price levels in
all models where it is included. Since it is the UN-initiated crisis rather than the North Koreainitiated crisis (which was not significant for either Pollock or cabbage), it may be the case
that an externally initiated, sharp but short crisis (and the siege mentality that accompanies it)
does have an effect on North Korea's internal markets, rendering it difficult for the North
Korean state to react in time, and making it more difficult for food to get to market. Sanctions,
!
17!
on the other hand, last longer (in fact, they are a one-way ratchet from North Korea's
perspective), meaning that there is more time for the North Korean regime and businesses to
adapt (which explains why sanctions decrease price levels for cabbage). This suggests that
North Korea does pay a domestic price for short-term crises even if it is able to compensate
for the effects of sanctions, and even if (as in the case of China's smuggling crackdown and
its effect on rice and pork prices) China aids in circumventing those sanctions.
CONCLUSION
It is clear that the regime is not capable of insulating Pyongyang residents entirely
from sanctions and crises. Sanctions do seem to have an effect, and may be forcing the
government or private suppliers to compensate. If the purpose is to impose costs on the North
Korean elite population, then their effect is noticeable, possibly because North Korea is such
an isolated country, and isolated countries see larger effects from sanctions that non-isolated
countries (Afesorgbor and Mahadevan, 2016). Even if sanctions do not appear to be enough
to destabilize the regime, the regime (or at least the markets) must compensate for greater
difficulty in accessing imported goods by switching to domestic goods. China, long
considered the key to constraining North Korea's behavior, had made its displeasure known
through a number of ‘crackdowns,’ but their effects appear to undercut the sanctions
themselves (at least for imported goods). The fact that effects in food prices of crises and
sanctions exist at all in Pyongyang suggests that North Korea is not wholly isolated from the
rest of the world. Moreover, the fact that the effects can be seen relatively quickly potentially
demonstrate North Korea’s dependence on China. Given the opacity of the North Korean
regime, it is basically impossible to examine directly the mechanism by which the regime
stays in power and pays off its elites, so the hypotheses put forward in this paper are at best
guesses waiting for greater in-depth examination of North Korean domestic politics.
More generally, the results suggest that escalating economic sanctions do have a
relatively quick effect even on what are generally considered to be isolated countries.
However, sanctions should not necessarily therefore be thought of as an appropriate hammer
to beat down all nails. The results confirm that the sanctioned regimes are likely to have
methods to adapt to sanctions and maintain the economic wellbeing of their core supporters,
even in the face of robust measures. They also suggest that the economic losses from
provocations by sanctioned regimes may be sustainable, and thus serve as no incentive to
refrain from provocations.
!
18!
APPENDIX
Table A.1: The effect of internal and external shocks on rice prices and their variability
variable
A.1
A.2
A.3
A.4
A.5
B.1
B.2
B.3
B.4
B.5
B.6
B.7
B.8
B.9
B.10
B.11
B.12
Dependent Variable: price levels (log-differences)
unsanc
0.009*
(0.005)
0.010*
(0.006)
0.014
(0.009)
0.013
(0.008)
0.014
(0.009)
0.017*
(0.009)
0.015*
(0.009)
0.013
(0.008)
0.019**
(0.008)
0.014*
(0.008)
0.010
(0.007)
0.020***
(0.006)
0.012*
(0.007)
kjupow
0.005
(0.018)
0.008
(0.019)
0.011
(0.020)
0.008
(0.019)
-0.004
(0.019)
0.006
(0.019)
0.011
(0.020)
-0.004
(0.020)
0.009
(0.020)
0.005
(0.019)
-0.001
(0.018)
0.004
(0.019)
jstpur
-0.005
(0.014)
-0.014
(0.020)
-0.014
(0.018)
-0.013
(0.020)
-0.022
(0.019)
-0.015
(0.020)
-0.013
(0.019)
-0.025
(0.018)
-0.016
(0.019)
-0.006
(0.017)
-0.028*
(0.015)
-0.009
(0.015)
-0.015
(0.022)
0.011
(0.020)
-0.010
(0.020)
-0.014
(0.019)
0.006
(0.018)
-0.011
(0.018)
eusanc
0.002
(0.003)
ussanc
0.005*
(0.003)
cr2013
0.009
(0.011)
ms2013
-0.013
(0.020)
0.006
(0.010)
-0.013
(0.017)
enfor
0.005
(0.020)
0.003
(0.019)
bankcr
-0.002
(0.018)
-0.015
(0.030)
smugcr
-0.015
(0.030)
-0.088***
(0.024)
-0.019
(0.029)
-0.086***
(0.024)
-0.084***
(0.023)
Dependent Variable: price variability (coefficient of variation)
unsanc
0.001
(0.002)
0.003
(0.002)
-0.003
(0.004)
0.000
(0.003)
-0.004
(0.004)
-0.003
(0.004)
-0.003
(0.004)
-0.003
(0.003)
0.000
(0.003)
0.000
(0.003)
-0.002
(0.003)
0.003
(0.003)
0.003
(0.003)
kjupow
0.001
(0.007)
0.000
(0.007)
-0.001
(0.007)
0.000
(0.007)
0.000
(0.007)
0.000
(0.007)
0.000
(0.007)
-0.001
(0.007)
-0.001
(0.007)
0.001
(0.007)
0.001
(0.007)
0.001
(0.007)
jstpur
-0.009
(0.006)
0.002
(0.008)
-0.003
(0.007)
0.004
(0.008)
0.001
(0.008)
0.002
(0.008)
0.002
(0.008)
-0.004
(0.008)
-0.004
(0.007)
-0.001
(0.007)
-0.010*
(0.006)
-0.010*
(0.006)
0.011
(0.009)
0.018**
(0.008)
0.018**
(0.008)
0.006
(0.007)
0.010
(0.007)
0.010
(0.007)
eusanc
-0.001
(0.001)
ussanc
cr2013
ms2013
enfor
0.000
(0.001)
0.013***
(0.005)
0.017**
(0.008)
0.011**
(0.005)
0.010
(0.007)
0.015*
(0.009)
0.018**
(0.008)
bankcr
smugcr
!
0.020**
(0.008)
-0.007
(0.012)
-0.009
(0.011)
-0.004
(0.012)
-0.005
(0.011)
-0.005
(0.012)
-0.007
(0.011)
19!
Table A.2: The effect of internal and external shocks on pork prices and their variability
variable
A.1
A.2
A.3
A.4
A.5
B.1
B.2
B.3
B.4
B.5
B.6
B.7
B.8
B.9
B.10
B.11
B.12
Dependent Variable: price levels (log-differences)
unsanc
0.005
(0.005)
0.017**
(0.007)
0.013
(0.009)
0.014*
(0.008)
0.011
(0.009)
0.015*
(0.009)
0.014
(0.009)
0.010
(0.008)
0.017**
(0.008)
0.016**
(0.008)
0.010
(0.008)
0.020***
(0.007)
0.019***
(0.007)
kjupow
-0.005
(0.016)
-0.005
(0.016)
-0.006
(0.016)
-0.005
(0.016)
-0.007
(0.016)
-0.007
(0.016)
-0.006
(0.016)
-0.008
(0.016)
-0.008
(0.016)
-0.006
(0.016)
-0.006
(0.016)
-0.006
(0.016)
jstpur
-0.039***
(0.013)
-0.032*
(0.018)
-0.033*
(0.017)
-0.028
(0.018)
-0.036**
(0.018)
-0.036**
(0.018)
-0.026
(0.017)
-0.039**
(0.017)
-0.038**
(0.017)
-0.026
(0.016)
-0.048***
(0.014)
-0.045***
(0.014)
-0.005
(0.019)
0.017
(0.017)
0.014
(0.017)
-0.001
(0.015)
0.013
(0.013)
0.011
(0.013)
eusanc
-0.001
(0.003)
ussanc
0.002
(0.003)
cr2013
0.029***
(0.011)
ms2013
0.009
(0.016)
0.024**
(0.010)
0.008
(0.013)
enfor
0.028
(0.019)
0.025
(0.018)
bankcr
0.025
(0.016)
-0.036
(0.025)
smugcr
-0.036
(0.025)
-0.042**
(0.021)
-0.032
(0.024)
-0.041*
(0.021)
-0.037*
(0.020)
Dependent Variable: price variability (coefficient of variation)
unsanc
0.002
(0.002)
0.002
(0.002)
-0.001
(0.003)
0.001
(0.003)
-0.002
(0.003)
-0.001
(0.003)
-0.001
(0.003)
-0.001
(0.003)
0.001
(0.003)
0.001
(0.003)
-0.001
(0.003)
0.002
(0.002)
0.003
(0.002)
kjupow
0.003
(0.006)
0.002
(0.006)
0.002
(0.006)
0.003
(0.006)
0.002
(0.006)
0.002
(0.006)
0.003
(0.006)
0.002
(0.006)
0.002
(0.006)
0.003
(0.006)
0.003
(0.006)
0.003
(0.006)
jstpur
-0.003
(0.005)
0.004
(0.007)
0.001
(0.006)
0.006
(0.007)
0.004
(0.007)
0.004
(0.007)
0.005
(0.006)
0.000
(0.006)
0.000
(0.006)
0.005
(0.006)
-0.003
(0.005)
-0.003
(0.005)
0.003
(0.007)
0.010*
(0.006)
0.010*
(0.006)
0.000
(0.005)
0.005
(0.005)
0.005
(0.005)
eusanc
0.000
(0.001)
ussanc
cr2013
ms2013
enfor
0.000
(0.001)
0.008**
(0.004)
0.010*
(0.006)
0.006**
(0.003)
0.005
(0.005)
0.014**
(0.007)
0.015**
(0.007)
bankcr
smugcr
!
0.015**
(0.006)
-0.004
(0.010)
-0.003
(0.009)
-0.003
(0.010)
-0.001
(0.009)
-0.001
(0.010)
0.000
(0.008)
20!
Table A.3: The effect of internal and external shocks on pollock prices and their variability
variable
A.1
A.2
A.3
A.4
A.5
B.1
B.2
B.3
B.4
B.5
B.6
B.7
B.8
B.9
B.10
B.11
B.12
Dependent Variable: price levels (log-differences)
unsanc
-0.001
(0.002)
-0.001
(0.002)
-0.004
(0.004)
-0.001
(0.003)
-0.004
(0.004)
-0.004
(0.004)
-0.003
(0.004)
-0.002
(0.003)
-0.001
(0.003)
-0.001
(0.003)
-0.001
(0.003)
-0.001
(0.003)
0.000
(0.003)
kjupow
-0.004
(0.007)
-0.004
(0.007)
-0.004
(0.007)
-0.004
(0.007)
-0.004
(0.007)
-0.005
(0.007)
-0.004
(0.007)
-0.004
(0.007)
-0.005
(0.007)
-0.004
(0.007)
-0.004
(0.007)
-0.004
(0.007)
jstpur
-0.002
(0.006)
0.003
(0.008)
-0.001
(0.008)
0.003
(0.008)
0.003
(0.008)
0.003
(0.008)
-0.001
(0.008)
-0.001
(0.008)
-0.002
(0.008)
-0.001
(0.007)
-0.003
(0.006)
-0.004
(0.006)
0.009
(0.009)
0.009
(0.008)
0.009
(0.008)
0.001
(0.007)
0.002
(0.006)
0.003
(0.006)
eusanc
-0.001
(0.001)
ussanc
-0.001
(0.001)
cr2013
0.002
(0.005)
ms2013
0.008
(0.008)
0.000
(0.004)
0.002
(0.006)
enfor
-0.002
(0.009)
0.001
(0.008)
bankcr
0.002
(0.007)
-0.010
(0.011)
smugcr
-0.008
(0.011)
-0.004
(0.010)
-0.007
(0.011)
-0.002
(0.010)
-0.001
(0.009)
Dependent Variable: price variability (coefficient of variation)
unsanc
0.000
(0.001)
0.000
(0.001)
0.001
(0.002)
0.000
(0.001)
0.001
(0.002)
0.001
(0.002)
0.001
(0.002)
0.001
(0.001)
0.001
(0.001)
0.001
(0.001)
0.000
(0.001)
0.000
(0.001)
0.000
(0.001)
kjupow
0.004
(0.003)
0.004
(0.003)
0.004
(0.003)
0.004
(0.003)
0.004
(0.003)
0.004
(0.003)
0.004
(0.003)
0.004
(0.003)
0.004
(0.003)
0.004
(0.003)
0.004
(0.003)
0.004
(0.003)
jstpur
-0.001
(0.002)
-0.003
(0.003)
-0.002
(0.003)
-0.003
(0.003)
-0.003
(0.003)
-0.003
(0.003)
-0.003
(0.003)
-0.003
(0.003)
-0.003
(0.003)
-0.002
(0.003)
-0.002
(0.003)
-0.001
(0.003)
-0.001
(0.004)
-0.002
(0.003)
-0.002
(0.003)
-0.001
(0.003)
-0.002
(0.003)
-0.002
(0.003)
eusanc
0.000
(0.000)
ussanc
cr2013
ms2013
enfor
0.000
(0.000)
0.001
(0.002)
-0.002
(0.003)
0.001
(0.002)
-0.002
(0.003)
-0.001
(0.004)
-0.001
(0.003)
bankcr
smugcr
!
-0.002
(0.003)
-0.001
(0.005)
-0.001
(0.004)
-0.001
(0.005)
-0.001
(0.004)
-0.002
(0.005)
-0.002
(0.004)
21!
Table A.4: The effect of internal and external shocks on cabbage prices and their variability
variable
A.1
A.2
A.3
A.4
A.5
B.1
B.2
B.3
B.4
B.5
B.6
B.7
B.8
B.9
B.10
B.11
B.12
Dependent Variable: price levels (log-differences)
unsanc
-0.004
(0.005)
-0.007
(0.006)
-0.019**
(0.009)
-0.014*
(0.008)
-0.019**
(0.009)
-0.019**
(0.009)
-0.019**
(0.009)
-0.014*
(0.008)
-0.013
(0.008)
-0.013
(0.008)
-0.010
(0.008)
-0.006
(0.007)
-0.006
(0.006)
kjupow
0.025
(0.019)
0.025
(0.019)
0.023
(0.019)
0.024
(0.019)
0.024
(0.019)
0.024
(0.019)
0.023
(0.019)
0.022
(0.019)
0.022
(0.019)
0.026
(0.019)
0.025
(0.019)
0.025
(0.019)
jstpur
0.005
(0.014)
0.031
(0.020)
0.022
(0.018)
0.030
(0.020)
0.030
(0.020)
0.030
(0.020)
0.022
(0.019)
0.020
(0.019)
0.020
(0.018)
0.011
(0.017)
0.004
(0.015)
0.004
(0.015)
0.038*
(0.021)
0.037*
(0.019)
0.037*
(0.019)
0.022
(0.016)
0.024
(0.015)
0.023
(0.015)
eusanc
-0.002
(0.003)
ussanc
-0.001
(0.002)
cr2013
0.008
(0.011)
ms2013
0.034*
(0.018)
0.008
(0.010)
0.022
(0.015)
enfor
-0.008
(0.021)
0.001
(0.020)
bankcr
0.012
(0.018)
-0.018
(0.027)
smugcr
-0.015
(0.027)
-0.015
(0.023)
-0.008
(0.027)
-0.012
(0.023)
-0.004
(0.023)
Dependent Variable: price variability (coefficient of variation)
unsanc
0.007***
(0.002)
0.006***
(0.002)
0.011***
(0.004)
0.009***
(0.003)
0.011***
(0.004)
0.011***
(0.004)
0.011***
(0.004)
0.009***
(0.003)
0.009***
(0.003)
0.009***
(0.003)
0.008***
(0.003)
0.007**
(0.003)
0.006**
(0.003)
kjupow
-0.005
(0.007)
-0.005
(0.007)
-0.004
(0.007)
-0.005
(0.007)
-0.005
(0.007)
-0.004
(0.007)
-0.004
(0.007)
-0.004
(0.007)
-0.004
(0.007)
-0.005
(0.007)
-0.005
(0.007)
-0.005
(0.007)
jstpur
0.005
(0.006)
-0.004
(0.008)
-0.001
(0.007)
-0.004
(0.008)
-0.004
(0.008)
-0.003
(0.008)
-0.002
(0.008)
-0.002
(0.008)
-0.001
(0.008)
0.002
(0.007)
0.004
(0.006)
0.006
(0.006)
-0.013
(0.009)
-0.012
(0.008)
-0.013
(0.008)
-0.008
(0.007)
-0.009
(0.006)
-0.009
(0.006)
eusanc
0.004***
(0.001)
ussanc
cr2013
ms2013
enfor
0.003***
(0.001)
-0.001
(0.005)
-0.012
(0.008)
-0.003
(0.004)
-0.009
(0.006)
0.001
(0.009)
-0.002
(0.008)
bankcr
smugcr
!
-0.006
(0.007)
0.006
(0.011)
-0.001
(0.010)
0.006
(0.011)
-0.002
(0.010)
0.003
(0.011)
-0.004
(0.009)
22!
Table A.5: Variables used in the analysis
Variable
date
time
rice
pork
pollock
cabbage
UN_sanctions
China_enforcement
JST_purge
2013_crisis
2013_crisis_missile
China_smugglingcrackdown
China_bankingcrackdown
2009_restrictions
Pyongyang_precipitation
WonPerUSD
KJU_power
DailyNK_rice
data_source
pork_corrected
!
Explanation
Date
Day count
Rice price in North Korean won
Pork price in North Korean won; per 100 grams before
5 July 2014, per 1 kg after 5 July 2014 (see
pork_corrected)
Pollock price in North Korean won
Cabbage price in North Korean won
0 = Pre-2013 UN sanctions are in place; 1 = UNSCR
2087 in effect; 2 = UNSCR 2094 in effect
1=China publicly enforces sanctions against North
Korea; 0=China is not taking any obvious steps to
enforce sanctions
0=Jang Song-Thaek is still alive; 1=Jang Song-thaek
has been purged
0=2013 crisis is not occurring; 1=2013 crisis is
occurring (range: UN sanctions imposed in January
2013 until Kaesong is reopened in September 2013)
0=2013 crisis is not occurring; 1=2013 crisis is
occurring (range: North Korea launches a missile in
December 2012 until Kaesong is reopened in
September 2013)
1=China cracks down on smuggling between China
and North Korea
1=China cracks down on North Korean financial
accounts in China
1=Restrictions on the operation of markets following
the November 2009 currency reform; 0=Restrictions
have been lifted
Daily precipitation in Pyongyang in mm (continuous)
Black market exchange rate of North Korean won per
US dollar
Kim Jong-un in power (dummy, 1=Kim Jong-un is
North Korean leader)
Rice price in North Korean won
Categorical variable for sources of data.
Source
Chinese investor
Chinese investor
Chinese investor
Chinese investor
Journalistic accounts
Journalistic accounts
Journalistic accounts
Journalistic accounts
Journalistic accounts
Journalistic accounts
Journalistic accounts
Journalistic accounts
South Korean
meteorological
service
DailyNK
Journalistic accounts
DailyNK
Two sources were
used: Chinese
investors group 1=1
(1 January 2010-31
December 2011);
Chinese investors
group 2=2 (1 January
2012-5 July 2014);
Chinese investors
groups 1=3 (6 July
2014-17 May 2015)
Prices corrected to account for different units used
across data sources
23!
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!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
1
See http://www.refworld.org/type,COUNTRYREP,,PRK,,,0.html for a compilation of information on North Korea.
See http://reliefweb.int/country/prk for a compilation of data-based reports on North Korea.
2!The fluctuation of the rice prices collected from Chinese investors correlate with the prices quotes by DailyNK.
The prices collected by the second group of Chinese investors are consistently higher than the DailyNK prices, but
the changes from day to day are the same, suggesting the second group of Chinese investors may be collecting the
same price information, but for a different weight unit. In any case, since we control for data source and are
interested in price changes rather than overall price, this is fairly immaterial to the analysis.
3
See DailyNK data at http://www.dailynk.com/english/market.php.
4
See the SanctionsWiki at http://www.sanctionswiki.org/North_Korea.
5
This is according to the Chinese investors who provided the data.
!
27!
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
6
China's banking crackdown has no effect, suggesting that financing purchases is not an issue per se for North
Korean food producers and importers, or that China may not have actually cracked down on finance. See Moore,
Malcolm. 13 April 2013. China breaking UN sanctions to support North Korea. The Telegraph (UK)..
!
28!