HIAS-E-129

Nutrient deficiencies and compositionalvariability in fertilizers: The case of the Mekong
Delta in Vietnam
Yukichi Mano(a), Yutaka Arimoto(a), Nguyen Duy Can(b), Do Van Hoang(b),Emi Kojin(c), Nguyen Thiet(b), Kazunari Tsukada(c), Vo Hong Tu(b)(c)(a) Hitotsubashi University(b) Can Tho University

Institute of Developing Economies,JETRO

April 2023

Hitotsubashi Institute for Advanced Study, Hitotsubashi University
2-1, Naka, Kunitachi, Tokyo 186-8601, Japan
tel:+81 42 580 8668 http://hias.hit-u.ac.jp/
HIAS discussion papers can be downloaded without charge from:https://hdl.handle.net/10086/27202
https://ideas.repec.org/s/hit/hiasdp.html

Nutrient deficiencies and compositional variability in fertilizers:
The case of the Mekong Delta in Vietnam
Yukichi Mano, Yutaka Arimoto, Nguyen Duy Can, Do Van Hoang, Emi Kojin, Nguyen Thiet, ,Kazunari Tsukada, Vo Hong Tu

April 23, 2023
Abstract
Quality control in fertilizer markets is critical to food security by facilitating fertilizer applicationand increasing agricultural productivity. With the active proliferation of new fertilizer producers,
Vietnam has also faced this problem, but public and market initiatives have recently been taken
to address the issue This paper evaluates the quality of 141 randomly sampled fertilizers in the
Mekong Delta, the country’s central rice producing area. We intentionally sampled unbranded
products to focus on the most vulnerable market segment. On average, our sample contains thelabeled nutrient content. However, the quality variability is high, and half of the sample has atleast one nutrient content below the legal requirement. We also find that nitrogen is overconcentrated and phosphate is diluted. These findings suggest that the quality of fertilizers in
Vietnam, even unbranded ones, is reliable on average, but efforts are needed to stabilize quality
variability. In addition, over-concentration of nitrogen may warrant policy attention as farmers
may inadvertently over-apply nitrogen and harm the environment.
Keywords: low-quality fertilizer, experience goods, Vietnam
JEL codes: L15, L51, Q16, Q18,

1

1. Introduction
Fertilizers are essential for improving agricultural productivity and food security (Evenson and
Gollin, 2003; Foster and Rosenzweig, 2010; Njeru et al., 2016). However, many developing
countries face the prevalence of low-quality fertilizers in the market or farmers’ (mis)perceptions
about them. These concerns inhibit the use of fertilizers, thereby, hampering farm productivity
and profitability. 1 Recent studies on fertilizer quality, focusing on sub-Saharan Africa (SSA),
show that farmers often underapply fertilizer because they believe it to be of poor quality withlow returns (Ashour et al., 2018; Ariga et al., 2019; Bold et al., 2017; Hoel et al., 2021; Michelson
et al., 2021; Ola and Menapace, 2020). Quality control in fertilizer markets is critical for
promoting agricultural development, ensuring a stable food supply, and improving the welfare ofagrarian economies. However, effective countermeasures are poorly understood, and practicalpolicies are not well established in developing countries. It is important to assess the fertilizer
quality in a context where initiatives have been taken to address the problem.
This study analyzes fertilizer quality in Vietnam, one of the world’s largest rice-producing andexporting countries, which has recently developed public and market initiatives to address
fertilizer quality issues (Kojin et al. 2023). We purchased 141 fertilizers from randomly selected
fertilizer retailers in the Mekong Delta region, Vietnam’s main rice production area. Our focus ison unbranded products, where the risk of low quality fertilizer penetration is high. We compared
the actual levels of three key nutrients - nitrogen, phosphate, and potassium - with the levels
declared on the labels. We also conducted in-depth interviews and discussions with stakeholders,
including government officials, fertilizer retailers, and farmers, to learn about fertilizer
governance, production, distribution, and use.
We find that the average nutrient content of our sample fertilizers, for each nutrient, is close
to the level indicated on the labels. However, the variability in quality is large. Half of the samples
did not meet the regulatory requirements for at least one nutrient. In particular, 6% of the samples
were missing the total of the three key nutrients by more than 10%, the legally acceptable level,

1

Other important barriers to fertilizer adoption include lack of knowledge and information, credit
constraints, costs, uncertain or lower than expected returns, and behavioral constraints. See Foster
and Rosenzweig (2010), Magruder (2018), and Macours (2019) for recent reviews of technology
adoption, including fertilizers in agriculture, and Jayne et al. (2018) and Holden (2019) for criticalreviews of fertilizer subsidies to promote adoption. Khor et al. (2018) identify risk aversion to
reduced fertilizer use among low-income farmers in Vietnam.
2

and had each key nutrient below the level indicated on the level, making them susceptible tointentional adulteration or mislabeling. Moreover, many samples suffer from variations in nutrient
composition: fertilizers have too much of some nutrients and too little of others. Fertilizer priceis positively correlated with its quality, but the relationship is weak, suggesting that fertilizer
quality is difficult to assess from price.
We attempt to determine why the nutrient composition varies within a sample. One possibility
is that granules are not stirred enough. We investigate this by comparing mixed and complex
fertilizers. Mixed fertilizers blend three granules of straight fertilizer for each nutrient, while
complex fertilizers contain all three nutrients in a single granule. Thus, mixed fertilizers are more
susceptible to greater nutrient variations. We find that the nutrient content of mixed fertilizers ismore variable than that of complex fertilizers, and that nitrogen appears to mask the lack ofphosphate. Although inconclusive, the evidence is consistent with unintentional compositionalvariation due to poor mixing or technical failure. We also discuss the possibility of intentionalvariation by producers to substitute cheap nutrients with expensive ones.
These results suggest that for the unbranded fertilizers in the Mekong Delta, the labels are (onaverage) reliable, but that we cannot rule out the possibility of simple adulteration by foreign
matter contamination or mislabeling. Farmers face a half chance of buying a product that is
substandard in at least one nutrient content, and the products often contain both over-concentrated
and diluted nutrients. The findings suggest the importance of technological upgrading to stabilize
quality.
Vietnam is an appropriate case to study fertilizer quality issues because it is a step ahead of
SSA in terms of agricultural development and governance of fertilizer quality. Rice yields in
Vietnam tripled between 1980 and 2020, in part due to intensified fertilizer use, with nitrogen
inputs increasing 20-fold (Section 2.2), despite a history of low fertilizer quality (Kojin et al.,2023, Table 1; Nguyen, 2017). Vietnam meets several criteria for the late stage of fertilizer market
development (Ariga et al., 2019). Kojin et al. (2023) detail the governance of fertilizer quality in
Vietnam, where large networks of fertilizer producers and agro-dealers have emerged in themarket under the control of current government policies and regulations. In addition, branded
products are well established in the Vietnamese fertilizer market, unlike in SSA, where farmers
do not pay much attention to brands. Therefore, the current status of fertilizer quality in the
Vietnamese market provides useful information for examining and discussing the effectiveness3

of such government and market initiatives.
This paper contributes to the growing literature on fertilizer (and agricultural input) quality(Ashour et al., 2019; Ariga et al., 2019; Bold et al., 2017; Michelson et al., 2021; Ola andMenapace, 2020). Key questions are the extent of fertilizer quality, the ability and accuracy offarmers to infer the quality from market signals and observable characteristics, and how and why
low-quality fertilizers or farmers’ (mis)perceptions persist. Most studies examine the case of SSA,
where both public and private initiatives to eliminate low-quality fertilizer are weak. We add tothe literature by estimating the prevalence of low-quality fertilizer in an Asian agricultural
economy with efforts to regulate fertilizer quality in the market. We complement a detailed
comprehensive description of the public and market initiatives to regulate fertilizer quality in
Vietnam (Kojin et al. 2023) by providing objective scientific evidence on fertilizer quality in themarkets.
We also contribute to the literature by proposing an idea for investigating whether the quality
deviations are caused by technical defects. Identifying whether the problem is an unintentional
technical problem is important because intentional quality dilution requires different policy
interventions such as regulation and inspection, whereas unintentional quality problems due toinadequate knowledge or technological defects may require technical training and support.
The remainder of this paper is organized as follows. Section 2 presents the conceptual
framework of the fertilizer quality problem and the background of the fertilizer market in Vietnam.
Section 3 explains the data. Section 4 describes the test results of fertilizer quality in the market.
Section 5 summarizes the results and discusses their implications.

2. Conceptual framework and background2.1. Fertilizers as “noisy” experience goods
We consider a fertilizer to be low quality if its nutrient content is below the level indicated on
the label and substandard if the content is below −10% of the level indicated on the label, whichis the legal lower limit as defined by Decree 108 (108/2017/NĐ-CP) in Vietnam. The productionof low-quality fertilizers may be intentional, when producers try to increase their profits by using
inappropriate ingredients or mixing in contaminants or additives. Technical deficiencies such as
inadequate technology, poor quality control, insufficient chemical knowledge, or improper4

storage or transportation could also be a reason for low-quality fertilizers. 2
Reputation mechanisms typically resolve adverse selection by removing lemons from themarket; consumers continue to buy a product until they discover that it is of low quality, andproducers or suppliers ensure the supply of high-quality products to maintain loyal consumers(i.e., reputation) (MacLeod, 2007). However, reputation mechanisms may not work for fertilizers
because consumers cannot accurately assess the product quality but only observe its noisy signals(e.g., crop growth), which are also influenced by other factors (e.g., soil nutrients, weather
conditions, and farming practices) (Bold et al., 2017). 3 As a result, low-quality fertilizers may
dominate the market, and farmers may find it difficult to apply the optimal amount of fertilizer orbe discouraged from applying fertilizers.
2.2. Agricultural production, fertilizer use, and governance in Vietnam
Agricultural production in Vietnam has expanded since the transition from a central planningto a socialist-oriented market economy, facilitated by the economic reforms known as doi moi in
1986. Rice production exceeded the policy targets after the start of doi moi, and Vietnam became
the world’s fifth-largest rice producer and the third-largest exporter in 2018 (Food and Agriculture
Organization of United Nations, 2023). Our study area, the Mekong Delta, is the largest rice bowl,
followed by the Red River Delta. The increase in rice production and yield in the early doi moi
period was driven by improved farmer motivation to produce rice and technologicalimprovements, such as the construction and maintenance of irrigation facilities, the adoption ofmodern varieties, and a rapid increase in fertilizer application.
Fertilizer production has responded to the increase in its demand (Kojin et al, 2023). Although
the supply of DAP (i.e., diammonium phosphate) is still dependent on imports, the domestic
supply of NPK (fertilizers containing nitrogen (N), phosphate (P), and potassium (K)), urea, andphosphate, which accounts for about 70% of fertilizer demand in Vietnam, exceeds domestic use(Bùi, 2019: 18-19; Vũ, 2018). 4
2

The concept of substandard/spurious/falsely labeled/falsified/counterfeit (SSFFC) proposed by
WHO (2011) for medical products is useful and comprehensive to address the problem.
3
This is a common problem with noisy experience goods like seeds, pesticides, herbicides(Ashour et al., 2019), or anti-malaria drugs (Björkman Nyqvist et al., 2022).
4
Large state-owned enterprises belonging to either the Vietnam National Chemical Group(VINACHEM) or the Vietnam Oil and Gas Group (PVN) and four other large enterprises account5

Figure 1 presents the fertilizer distribution channels in Vietnam, with the main channel
indicated by a bold arrow, based on our interviews. 5 The main intermediary channels of the largescale enterprises are agents (đại lý) with sufficient capital and retailers (cửa 6ang). Distributors(nhà phân phối) are another intermediary channel between large enterprises and agents orretailers. 6 In addition, there are few other channels: direct sales from large enterprises to farmers(who are often involved in contract farming or are large farmers) and distribution throughcooperatives. Small producers include emerging companies that are new to the business and are
more likely to produce fertilizers of lower quality or more unstable nutrient composition due toinadequate skills and technologies. They market their fertilizers through similar channels as large
producers and also through direct sales to farmers, which is a less regulated market channel. The
exact share of each channel is unknown due to a lack of data. However, all our informants agreed
that the channel indicated by the bold arrow is the main one. 7
for approximately 95% of the total fertilizer production in Vietnam (Vũ, 2018). VINACHEM
includes Habac Nitrogenous Fertilizer & Chemicals Company Ltd., Binh Dien Fertilizer Joint
Stock Company, Ninh Binh Nitrogenous Fertilizer Ltd. Company, Southern Fertilizer Corporation,
Van Dien Phosphate Corporation, Lam Thao Phosphate and Chemical JSC, Ninh Binh Phosphate
Fertilizer Joint Stock Company, Can Tho Fertilizer & Chemical Joint Stock Company, DAPVINACHEM Joint Stock Company, and DAP2-VINACHEM Joint Stock Company. The PVNGroup consists of PETROVIETNAM Fertilizer and Chemicals Corporation, andPETROVIETNAM Ca Mau Fertilizer Joint Stock Company. The other four large companies are
Five Star International Group, General Materials Biochemistry Fertilizer Joint Stock Company,
Banconco Group, and Japan Vietnam Fertilizer Company. Along with these major producers, we
also excluded major unlisted companies reported in FPT Securities (2015): Quang Binh Import& Export JSC, Que Lam Group, Agricultural Products, and Materials JSC (Apromaco), Song
Gianh Corporation, and Thien Sinh JSC.
5
We conducted interviews with fertilizer manufacturers, government officials, fertilizer retailers
and wholesalers, large-scale producers, farmers, cooperatives, and specialists in soil science andfertilizers in provinces in the Mekong Delta and Hanoi, in August 2018 and August 2019.
Retailers and farmers were introduced by local government officials following the standard
academic survey protocols in Vietnam.
6
Ihara (2020) details the intermediary channels of Vietnamese toiletries and indicates that
distributors are identified as warehousing and customer service providers in the relatively broad
market while retaining ownership of products. Agents are identified as entities selling products
on behalf of suppliers or distributors without physical possession of the products. This
classification could be adapted to fertilizer distribution, although there may be minor differences
across products.
7
The distribution channel of imported fertilizers is not well known, even among government
officials, fertilizer wholesalers and retailers, and other experts we interviewed. However, it is6

Figure 1. Fertilizer distribution channels in Vietnam
Source: Prepared by the authors based on the August 2018 interview survey.
Note: The bold arrow represents the main channel.

A comprehensive review of the media reports by Kojin et al. (2023) suggests that substandard
fertilizers have been on the market for over a decade. Violations include missing ingredients, fakepackaging of well-known brands, counterfeiting with silicone, and disguising the country of
production. Proposed reasons for the production of substandard fertilizers include inadequate
knowledge and technology of small-scale producers, collusion between producers and retailers,
importation of low-quality/counterfeit fertilizers, corruption in the authorized organizations that
conduct the fertilizer testing required for approval of distribution, insufficient penalties for
production and distribution of substandard fertilizers, and cheap taste of farmers, especially inremote areas.
Low-quality fertilizers (mainly NPK) can have negative economic and environmental impacts.
Nguyen (2017: 47) links low and unreliable quality to over-fertilization in Vietnam. Indeed,
Vietnam is an intensive fertilizer user, ranking fourth among Asian countries in 2016 (Food andlikely to be distributed through the same channels as domestic products. According to newspaper
reports, Chinese products account for approximately 50% of imported fertilizers (Minh, 2018).

7

Agriculture Organization of the United Nations, 2023). Using more fertilizer than recommended
increases production costs and reduces profits (Nguyen, 2017: 41–43; Stuart et al., 2018; Tran etal., 2018). Overfertilization also causes soil pollution, such as soil fertility loss (Hà et al., 2018)
and soil acidification (Crews and Peoples, 2004).
Given the prevalence of low-quality fertilizers, several initiatives are being taken to mitigate
the problem. Kojin et al. (2023) report that government controls, including licensing, mandatory
quality labeling, and random inspections, are being implemented. Market initiatives by producers
through branding, warranty, and dealer certification can help build and maintain reputations andenable farmers to identify better quality products. Kojin et al. (2023) also report on a mechanism
where poor quality goods are excluded through social-learning where farmers’ learning andfeedback to retailers help to update local retailers’ product assortment.

3. Data
We focus on the retail channel (Figure 1), which has the largest share of all distribution
channels. This channel has the potential to benefit the most from government initiatives targeting
licensed fertilizer retailers (see Section 2.2). In contrast, farmer cooperatives and contract farming
are relatively small channels and have innate internal incentives to distribute good quality
fertilizer even without government initiatives.
We randomly selected two districts from each of the five major agricultural provinces (AnGiang, Hậu Giang, Kiên Giang, Sóc Trăng, and Vĩnh Long) in the Mekong Delta. 8 We obtained
a list of certified fertilizer retailers from each district government 9 and randomly sorted the listed
retailers to determine the order of visits. Between November 2018 and April 2019, several local
coauthors visited the sampled retailers using a mystery shopper approach to purchase 1 kg from
50 kg bags of either NPK or DAP after mixing the fertilizer in the bags (Bold et al., 2017;
Michelson et al., 2021). Farmers typically purchase whole bags of fertilizer (typically 50 kg), butthey can also purchase fertilizer in smaller portions.
In selecting the sample, we deliberately focused on unbranded products to increase the prior

8

We excluded Can Tho city because it is exceptionally urbanized, regulations are strictly
implemented, and the marketing system seems well organized.
9
For Soc Trang province, we did not have access to the list of licensed fertilizer retailers.
Therefore, we thus randomly selected ten communes (xã) and randomly visited two retailers foreach commune.
8

probability of detecting low-quality fertilizers at each sample retailer. During our preliminaryinterviews, government officials, fertilizer manufacturers, retailers, and farmers indicated thatbranded fertilizers are most likely to meet quality standards because of regular inspections andmanufacturers’ warranties, but they are less certain about the quality of unbranded products.
Therefore, at each sample retailer, we excluded major fertilizer brands and purchased the cheapest
unbranded fertilizers available, which are often from small start-up producers. They may lack theknowledge and skills to produce proper fertilizers, or they may have a greater incentive to makeshort-term profits by supplying low-quality fertilizers. Note that our sampling strategy is
consistent with the recent studies in SSA, where farmers typically purchase cheap unbranded
fertilizers (Bold et al., 2017; Michelson et al., 2021).
If a retailer did not sell the fertilizer in small quantities (1 kg) or only sold major brands, weleft the store and visited the next retailer on the list. We repeated this process until the sample size
reached the target number of retailers, which is proportional to the total number of retailers ineach district. The limitations of this sampling method are discussed in Section 5.2. The purchased
fertilizer was double-sealed in a zip-lock bag after leaving the store. We also recorded the nameof the retailer, the date and time of the visit, the labeled nutrient composition (e.g., 16-16-8), themanufacturer or brand name, and the retail price.
The sampled fertilizers were immediately delivered to the Laboratory of Soil Chemistry,
Department of Social Science, Can Tho University, Vietnam. The nitrogen (N), phosphate (P),and potassium (K) contents of the sample fertilizers were measured, 10 and the results were

10

The laboratory used the following methods to measure each nutrient. N is the sum of urea,

NH4+ and NO3-. To measure the content level of urea, the sample was extracted with HCl 0.05N
at a ratio of 1:100, and then urea-N was determined by the colorimetric method on aspectrophotometer. For NH4+ and NO3-, the sample was extracted with HCl 0.05N at a ratio of
1:100, and then NH4+ and NO3- were determined by colorimetric method on spectrophotometer.
To determine the content level of P, the sample was digested with mixture of concentrated HNO3
+ HCl (1:3) and then H2SO4 8M was added. P in the digested sample was determined bycolorimetric method (molybdate blue method) on spectrophotometer. To measure K, the sample
was digested with a mixture of concentrated HNO3 + HCl (1:3), and then H2SO4 8M was added.
K in the digested sample was determined on atomic absorption spectrometer. The standard series
for the regression curve are prepared from standard chemicals to measure analytical error.

9confirmed by double testing. The nutrient test results were matched with information from theretailer survey, resulting in 141 observations for our analysis.
Table 1 describes the nutrient composition of the sample fertilizers as indicated on the label,the sampling location, the price, and whether it was a complex fertilizer. More than 61% of thesample had a 20-20-15 nutrient composition, and 10% were complex fertilizers, which contain all
nutrients in a single granule, as opposed to mixed fertilizers, which are made by physically mixing
granules of straight fertilizers for each nutrient. 11

Table 1. Basic statistics of sample fertilizers
Obs.

Share

16-16-08

141

0.142

20-20-15

141

0.610

25-25-05

141

0.121

Others141

0.128

An Giang

141

0.220

Hậu Giang

141

0.163

Kiên Giang

141

0.184

Fertilizer type

Province

Sóc Trăng

141

0.191

Vĩ nh Long

141

0.241

Obs.

Mean

S.D.

Price (1000VND/kg)

131

11.986

1.305

Complex fertilizer

134

0.097

dummy

Note: Observations for price and complex fertilizer are smaller due to missing price informationand sample image (photo) data.

11

It is easy to distinguish between complex fertilizers and mixed fertilizers by visual inspection
because mixed fertilizers contain separate granules with different colors for different nutrients.
We identified the fertilizer as “complex” if a fertilizer sample consisted of single granules.
10

4. Results
4.1. Quality deviation
As an indicator of fertilizer quality, we use the deviation rate (%), 𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝑖𝑖𝑖𝑖 , which measuresthe deviation of the actual nutrient content from the labeled nutrient content level:

𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝑖𝑖𝑖𝑖 =𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎
𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙− 𝑣𝑣𝑖𝑖𝑖𝑖
𝑣𝑣𝑖𝑖𝑖𝑖𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙
𝑣𝑣𝑖𝑖𝑖𝑖× 100

𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙
indicates the labeled level of the nutrient content 𝑗𝑗 ∈ {𝑁𝑁, 𝑃𝑃, 𝐾𝐾 } or the sum of thesewhere 𝑣𝑣𝑖𝑖𝑖𝑖

𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎
three nutrients in sample 𝑖𝑖 , and 𝑣𝑣𝑖𝑖𝑖𝑖
is the actual level revealed by our laboratory tests.

𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝑖𝑖𝑖𝑖 < 0 indicates that the actual 𝑗𝑗 content is below the labeled content level. We also

construct a substandard dummy variable, 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑖𝑖𝑖𝑖 ≡ 𝐼𝐼(𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝑡𝑡𝑒𝑒𝑖𝑖𝑖𝑖 < −10), indicating adeviation rate below −10%, which is the legally acceptable lower limit.

Table 2 reports the deviation rates and the proportion of the sample that is substandard. The

mean deviation rates for the whole sample are 3.20% (95% confidence interval (CI): 0.675-5.718)
for nitrogen, −7.75% (95% CI: −10.865–−4.640) for phosphate, and −1.38% (95% CI: −6.565–
3.806) for potassium (Panel A, column 1). While nitrogen is enriched, phosphate is more diluted
than the labeled level. The 95% confidence interval for phosphate exceeds the legal limit of −10%.
The mean deviation rate for the sum of these three nutrients is −2.5% (95% CI: −4.228-−0.675)(Panel A, column 1). Looking at the proportion of substandard samples, defined as those with adeviation rate below −10%, half (49%) of our samples have at least one substandard nutrient(Panel B, column 1). Phosphate is most likely to be deficient, with 33% of sample fertilizers being
substandard, followed by potassium (21%) and nitrogen (14%). If we add up the contents of thethree components (sum of N, P, and K) to calculate the aggregate deviation rate, 21% of thesamples are substandard. In Panel C, column 1 shows that 9.2% have at least one nutrient below−50% of the level indicated on the label. Deviation rates and proportions of substandard samples
vary by fertilizer type (columns 2−5), with no consistent pattern.

11

Table 2. Deviation rates and proportions of the substandard samples
(1)

(2)

(3)

(4)

(5)

By fertilizer types
Observations

All samples

16-16-08

20-20-15

25-25-05

Others

141

20

86

17

18

A. Mean deviation rate (%) (std. dev. In parenthesis)
Nitrogen (N)Phosphate (P)Potassium (K)Total (N+P+K)

3.20

4.34

4.82

0.14

-2.95

(15.1)(15.6)(16.0)(11.8)(11.9)

-7.75

-4.97

-8.36

-12.4

-3.54

(18.7)(10.5)(20.3)(16.7)(19.3)

-1.38

5.45

-7.02

7.55

9.55

(31.1)(32.1)(29.6)(43.5)(15.7)

-2.45

0.84

-3.20

-4.89

-0.22

(10.7)(9.31)(11.7)(9.92)(6.48)

B. Proportion of substandard samples (deviation rate < -10%)
Any of N, P, K

0.489

0.450

0.512

0.647

0.278

Nitrogen (N)

0.135

0.150

0.128

0.176

0.111

Phosphate (P)

0.333

0.250

0.349

0.588

0.111

Potassium (K)

0.206

0.200

0.256

0.118

0.056

Total (N+P+K)

0.206

0.100

0.244

0.235

0.111

C. Proportion of substandard samples (deviation rate < -50%)
Any of N, P, K

0.092

0.050

0.105

0.118

0.056

Nitrogen (N)

0.000

0.000

0.000

0.000

0.000

Phosphate (P)

0.028

0.000

0.035

0.000

0.056

Potassium (K)

0.078

0.050

0.093

0.118

0.000

Total (N+P+K)

0.000

0.000

0.000

0.000

0.000

Note: This table reports the mean (Panel A), the proportion of substandard samples with adeviation rate below −10% (Panel B), and the proportion of substandard samples with a deviation
rate below −50% (Panel C). The standard deviation is reported in the parentheses for Panel A.
Column 1 reports the statistics for the full sample. Columns 2−5 report the statistics by fertilizer
type.

12

Figure 2(a) presents the histograms of the nutrient deviation rates. Figure 2(b) depicts normal
probability-probability (P-P) plots to diagnose the distributions of the deviation rates against
normal distributions. Phosphate and potassium are more skewed to the left than the normal
distribution. Table 3 shows the skewness, kurtosis, and skewness/kurtosis tests for normality.
Negative skewness and normality tests indicate that the left tail of the distribution is indeed longer
for these two nutrients. However, it is important to note that almost 30% of the sample isconcentrated at a deviation rate of about 0%. In other words, about one-third of the sample isaccurately produced at the exact content level as labeled.
The finding that 21% of the samples are substandard for the sum of three nutrients is alarming.
Of these 29 substandard samples, 8 samples (28%, or 6% of all 141 samples) were deficient in all
three nutrients (Table 4). 12 Since all nutrients are diluted together, these samples could be a
product of simple dilution by the addition of foreign matter such as sand. Another possibility isintentional or unintentional mislabeling, such as 16-16-8 fertilizers being labeled as 20-20-15.
However, for the vast majority (72%) of the substandard samples based on the aggregateddeviation rate, we see that some nutrients are over-concentrated, while others are diluted. Thispattern is inconsistent with simple dilution or mislabeling.
In summary, our results have three implications. First, on average, farmers can rely on the label.
Second, we cannot completely rule out the possibility of deliberate dilution or mislabeling. Third,
farmers have a half chance of buying a product with at least one nutrient content below the legal
limit. Overall, the biggest problem is the variability in nutrient composition: some nutrients are
in excess, while others are deficient.

12

These are samples with id 4, 6, 7, 11, 15, 23, 24, and 29.
13

Figure 2. Distribution of deviation rates by nutrient
Note: Panel (a) depicts histograms of the deviation rates. The dashed vertical lines at −10%indicate the legally permissible level of the deviation rate. Panel (b) shows the normal P-P plots.
The y-axis is the cumulative distribution of the samples. All points are plotted along the diagonalline if the data are normally distributed.

Nitrogen (N)Nitrogen (N)
.3

1.00

.2

0.50

0.75
0.25

.1

0.00

0

0.00

Phosphate (P)

0.50

0.75

1.00

Phospahte (P)

.3

1.00

.2

0.75
0.50

.1

Fraction

0.25

0.25

0

0.00
0.00

Potassium (K)
.3

0.25

0.50

0.75

1.00

Potassium (K)

.2

1.00

.1

0.75

0

0.25

0.50
0.00

N+P+K

0.00

0.25

0.50

0.75

1.00

0.75

1.00

.3

N+P+K

.2
.1
0
-100

-50

0

50

100

1.00
0.75
0.50
0.25
0.00
0.00

Deviation rate (%)(a) Disbribution of deviation rates

0.25

0.50

Theoretical cumulative distribution(b) Standardized normal P-P plots

14

Table 3. Diagnosis of the distributions of deviation rates
Note: This table shows the skewness and kurtosis tests for normality.
(1)

(2)

(3)

(3)

Deviation rate (%)
Nitrogen (N)Phosphate (P)Potassium (K)

N+P+K

141

141

141

141

Obs.
Mean

3.197

-7.753-1.379-2.451

S.D.

15.14718.69531.14310.670Skewness

0.480-2.093-1.327-1.124

Kurtosis

3.653

10.443

6.117

4.924

Prob. Skewness

0.01980.00000.00000.0000Prob. Kurtosis

0.10970.00000.00010.0020

Joint adj chi2(2)

7.35

59.47

33.38

24.92

Joint Prob>chi2

0.02530.00000.00000.0000

Table 4. Details of the deviation rates for substandard samples based on aggregate deviation rate
Note. The negative deviation rate is highlighted in red and the positive is highlighted in blue.
Seq..

Fertilizer

id

type

Nutrient contents
NitrogenPhosphate

Deviation rates (%)

Pottasium

N+P+K

NitrogenPhosphate

Pottasium

N+P+K

1 20-20-15

28.5

0.0

0.3

28.8

43

-100

-98

-48

2 20-20-15

19.3

0.6

15.9

35.8

-4

-97

6

-35

3 20-20-15

29.0

9.5

1.3

39.8

45

-52

-92

-28

4 20-20-15

15.2

13.3

11.6

40.1

-24

-34

-23

-27

5 25-25-05

26.0

14.0

0.2

40.2

4

-44

-97

-27

6 20-20-15

19.3

10.2

10.6

40.1

-4

-49

-29

-27

7 20-20-15

18.1

13.5

9.8

41.4

-9

-33

-35

-25

8 20-20-15

24.7

17.5

0.9

43.1

24

-13

-94

-22

9 25-25-05

21.5

15.3

6.6

43.4

-14

-39

32

-21

10 16-16-08

16.3

11.2

4.5

32.0

2

-30

-44

-20

11 20-20-15

18.0

14.2

12.1

44.3

-10

-29

-19

-19

12 20-20-15

25.7

18.0

1.1

44.8

29

-10

-92

-18

13 20-20-15

24.7

19.9

0.5

45.1

24

-1

-97

-18

14 20-20-15

21.0

13.8

10.6

45.4

5

-31

-29

-17

15 20-20-15

18.4

14.6

12.7

45.7

-8

-27

-15

-17

16 16-16-08

12.4

12.8

8.1

33.3

-23

-20

1

-17

17 Others

20.0

4.8

23.3

48.1

-9

-76

55

-16

18 25-25-05

26.3

20.0

0.3

46.6

5

-20

-94

-15

19 20-20-15

25.1

21.1

0.4

46.6

26

6

-97

-15

20 20-20-15

23.3

13.0

11.1

47.4

16

-35

-26

-14

21 25-25-05

24.7

17.9

5.0

47.6

-1

-28

1

-13

22 Others

9.4

16.3

16.1

41.8

-41

2

1

-13

23 20-20-15

19.6

14.5

14.0

48.1

-2

-28

-7

-13

24 20-20-15

16.5

18.2

13.7

48.4

-18

-9

-9

-12

25 20-20-15

16.8

16.7

15.0

48.5

-16

-16

0

-12

26 20-20-15

15.0

18.5

15.0

48.5

-25

-8

0

-12

27 20-20-15

15.9

16.8

15.9

48.6

-21

-16

6

-12

28 20-20-15

14.9

17.2

16.6

48.7

-26

-14

11

-11

29 20-20-15

17.9

19.4

12.0

49.3

-11

-3

-20

-10

15

4.2. Price and quality deviation
Figure 3 depicts the relationship between the logged price and the deviation rates. Sample
fertilizers with higher quality deviations tend to have higher prices. Table 5 shows the estimation
results of a simple regression of price on deviation rate. Regional dummies are not included dueto the small sample size. On average, sample fertilizers with ten percentage points higher
deviation rates tend to have prices that are 0.1%–0.6 % higher. Columns 5 and 6 regress thesubstandard dummy on the logged price with threshold deviation rates of −10% and −50%,
respectively. Substandard samples at the −10% threshold tend to be 0.27% cheaper than thecompliant samples. However, the estimates are not significant in any case. Thus, price signals
quality to some extent, but not precisely.

Figure 3. Price and deviation rate
Nitrogen (N)2.8

Phosphate (P)Potassium (K)

N+P+K

ln(price)

2.6

2.4

2.2
-40

-20

0

20

40

-100

-50

0

50

-100

-50

0

Deviation rate (%)
ln(price)

Fitted values

16

50

100

-40

-20

0

20

Table 5. Correlation between price and quality
(1)

(2)

(3)

(4)

(5)

(6)

Deviation rate (%)
Nitrogen (N)0.000598(0.000576)

Phosphate (P)0.000629(0.000467)

Potassium (K)0.000119(0.000232)

Total (N+P+K)

0.00132(0.000763)

Substandard dummy
Deviation rate <-10%-0.0276(0.0193)

Deviation rate <-50%-0.00293(0.0230)

Constant

2.476***

2.482***

2.478***

2.480***

2.491***

2.478***(0.0103)(0.0105)(0.00974)(0.00983)(0.0135)(0.0104)

Observations

131

131

131

131

131

131

R-squared

0.007

0.011

0.001

0.016

0.016

0.000

Note: The outcome variable is the log (price), and its sample size is 131. The explanatory variablefor columns 1–4 is the deviation rate (%) for the specified nutrient. The explanatory variable forcolumns 5 and 6 is a substandard dummy indicating that at least one nutrient is 10% and 50% lessthan the labeled amount. Robust standard errors are shown in parentheses. ∗ 𝑝𝑝 < 0.05, ∗∗ 𝑝𝑝 <0.01, ∗∗∗ 𝑝𝑝 < 0.001.

17

4.3. Compositional variations between mixed and complex fertilizers
Our results suggest that the main problem is variation in nutrient composition: some fertilizers
contain too much of some nutrients and too little of others. We investigate whether there are any
systematic patterns in these compositional variations. An important question is whether thequality variations are intentional or merely due to technological defects in production and quality
management.
One possible cause of unintentional variation in deviation rates is inadequate stirring ofstraight fertilizers of different nutrients during the blending process of mixed fertilizers. 13 With
inadequate stirring, nutrient composition can vary from bag to bag, even if a producer has usedadequate amounts of each nutrient; for example, some bags may contain too much nitrogen whileothers may contain too little.
The key idea behind detecting these unintentional quality variations is that compositionalvariations are more likely to occur in mixed fertilizers, which simply mix straight fertilizers ofdifferent nutrients, than in complex fertilizers, which combine three nutrients in one granule. 14
Thus, if insufficient stirring is the main cause of quality diversity, we expect an apparent negative
correlation of the deviation rates between nutrients contained in a sample fertilizer for mixed
fertilizers, but not for complex fertilizers. To this end, we examine the distributions of multiple
nutrients contained, in contrast to existing studies that focus only on the distribution of nitrogen(Ariga et al. 2019; Bold et al. 2017; Michelson et al. 2021).
We find two differences between mixed and complex fertilizers (Table 6). First, mixed
fertilizers have greater variability in deviation rates than complex fertilizers. Table 6, panel (a)shows that the mean and standard deviation of the absolute deviation rates for all three nutrientsare larger for mixed fertilizers. Second, the compositional variation, which we mean by the
distribution of the deviation rates among nutrients within a sample, is also greater. For each sample𝑖𝑖, we first calculate the mean of three absolute deviation rates for each nutrient. We then take thesample average of these means and standard deviations, separately for mixed and complex

13

Similar compositional variations can occur due to segregation of nutrient granules within abag of mixed fertilizer during transport or storage; heavier granules fall below lighter granules
within each bag. However, we stirred the fertilizers well before sampling, so we rule out thischannel.
14
Compositional variations due to poor stirring of nutrients can also occur with complex
fertilizers before three nutrients are compunded into granules.
18

fertilizers. The mean absolute deviation rate for mixed fertilizers is higher than for complex
fertilizers (15.1% vs. 9.9%; panel (b)). These observations indicate that mixed fertilizers havegreater variability in deviation rates, both for each nutrient and for the nutrient composition. Thisis consistent with the idea that mixed fertilizers are more susceptible to inadequate stirring, orwith the view that the production of complex fertilizers requires more advanced technology andthese producers have better manufacturing precision. 15
If poor stirring is the cause of the quality deviation, we would expect to see a negative
correlation of the deviation rates between nutrients within a sample (i.e., if there is an excess of
one nutrient, then we should observe a deficiency of others), but such a correlation should beobserved for mixed fertilizers but not for complex fertilizers (because three nutrients arecompounded in one granule). Figure 4 shows the deviation rates between the three sets of binary
combinations of nutrients, and nitrogen vs. phosphate and potassium, by complex and mixed
fertilizer. It is clear from the figure that the deviation rates are more limited for complex fertilizers
than for mixed fertilizers, indicating the superior quality of complex fertilizers. Table 7 reports
the estimation results of the regression of the deviation rates of nitrogen (N) or potassium (K) on
the deviation rates of the remaining nutrients. The relationship between the deviation rates iscomplex. We observe a significant negative correlation between the deviation rates of nitrogenand potassium, or nitrogen and the remaining two nutrients, potassium and phosphate (P) formixed fertilizers. The correlations between nutrients for complex fertilizers are null except for thesubstitution between phosphate and potassium. Overall, while inconclusive, our results arearguably consistent with the pattern that may be caused by unintentional compositional variations
due to poor stirring particularly for mixed fertilizers.

15

Table 6, panels (c) to (e), also suggests that mixed fertilizers may be of lower quality thancomplex fertilizers, as indicated by more negative deviation rates for phosphate and potassium.
The proportion of substandard samples is also lower for complex fertilizers than for mixed
fertilizers (except for nitrogen).
19

Table 6. Comparison between mixed vs. complex fertilizers on quality
(1)

(2)

All samples

(3)

(4)

Complex fertilizers(n=141)(n=13)(5)(6)

Mixed fertilizers

(7)

(8)

(9)

Complex vs. mixed(n=121)

fertilizers

Mean

S.D.

Mean

S.D.

Mean

S.D.

Difference

S.E.

p -value

Nitrogen (N)11.28510.5569.150

11.41611.751

10.5272.601(3.212)

0.419

Phosphate (P)12.42915.951

7.365

6.569

13.20916.8145.843(2.337)0.014 *

Potassium (K)18.98724.672

13.21811.51320.44526.034

7.227(3.898)0.066

Total (N+P+K)

7.830

7.625

5.064

3.770

8.256

7.945

3.192

(1.245)0.011 *

14.62812.960

9.911

6.192

15.13513.4035.224(2.106)0.010 *(a) Absolute deviation rate (%)(b) Compositional variation
Mean absolute deviation rateof N, P, and K within sample(c) Deviation rate (%)
Nitrogen (N)

3.197

15.147-2.837

14.571

3.751

15.3586.588(4.155)0.115

Phosphate (P)-7.75318.695-0.78810.062-9.35819.244-8.57(3.222)0.009 **

Potassium (K)-1.37931.14313.21811.513-2.9

33.027-16.12(4.316)0.000 ***

Total (N+P+K)-2.451

10.67

1.504

6.289

-3.251

11.008-4.755(1.964)0.017 *(d) Sub-standard (Deviation rate < -10%)
At least one of NPK

0.489

0.502

0.308

0.480

0.529

0.501

0.221

(0.137)0.108

Nitrogen (N)

0.135

0.343

0.154

0.376

0.14

0.349

-0.0134(0.106)0.900

Phosphate (P)

0.333

0.473

0.231

0.439

0.364

0.483

0.133

(0.126)

0.292

Potassium (K)

0.206

0.406

0.000

0.000

0.231

0.423

0.231

(0.0386)0.000 ***

Total (N+P+K)

0.206

0.406

0.077

0.277

0.231

0.423

0.154

(0.0839)0.068(0.0284)

0.000 ***(e) Sub-standard (Deviation rate < -50%)
At least one of NPK

0.092

0.290

0.000

0.000

0.107

0.311

0.107

Nitrogen (N)

0.000

0.000

0.000

0.000

0.000

0.000

0

Phosphate (P)

0.028

0.167

0.000

0.000

0.033

0.18

0.0331(0.0164)0.046 *

Potassium (K)

0.078

0.269

0.000

0.000

0.091

0.289

0.0909(0.0263)0.001 ***

Total (N+P+K)

0.000

0.000

0.000

0.000

0.000

0.000

0

Note: Columns 1-6 report the mean and standard deviation. Columns 7-9 report the regression
coefficient and robust standard errors (in parentheses) regressing the outcome variables on themixed fertilizer dummy. ∗ 𝑝𝑝 < 0.05, ∗∗ 𝑝𝑝 < 0.01, ∗∗∗ 𝑝𝑝 < 0.001.

20

Figure 4. Correlation of deviation rates
50

100

Deviation rate (%): K

Deviation rate (%): P

50

0

-50

0

-50

Complex
Mixed

-100
-40

-20

0

Deviation rate (%): N

20

Complex
Mixed

-100
-40

40

-20

N vs. P

40

20

N vs. K

100

50

Deviation rate (%): P

Deviation rate (%): P+K

0

Deviation rate (%): N

0

-100

Complex
Mixed

-200
-40

-20

0

Deviation rate (%): N

20

0

-50

Complex
Mixed

-100
-100

40

-50

N vs. P+K

0

Deviation rate (%): K

50

100

K vs. P

Table 7. Correlation of deviation rates between nutrients
(1)

(2)

(3)

(4)

(5)

(6)

Deviation rate (%): N (nitrogen)All samples

ComplexMixed

All samples

Complex

Mixed

Deviation rate (%), N (nitrogen)Deviation rate (%), P (phosphate)
Deviation rate (%), K (potassium)

(8)

(9)

All samples

ComplexMixed-0.814***0.00000778-0.864***(0.194)(0.182)(0.225)0.02480.162

0.01340.318-0.769**0.327(0.0633)(0.466)(0.0642)(0.174)(0.185)(0.187)-0.201***0.0000224-0.195***(0.0411)(0.648)(0.0414)

Deviation rate (%), P + K
Constant(7)

Deviation rate (%): K (pottasium)-0.133***0.0485-0.134***(0.0341)(0.536)(0.0344)

3.112**-2.7103.310*

1.984-3.440

2.107

3.688

12.61***

3.398(1.187)(11.12)(1.293)(1.163)(9.341)(1.259)(2.228)(2.429)(2.650)Observations

141

13

121

141

13

121

141

13

121

R-squared

0.166

0.012

0.173

0.120

0.001

0.133

0.202

0.451

0.209

Note: The dependent variable is the deviation rate of phosphate (P) for columns 1–3 and thedeviation rate of potassium (K) for columns 4–6. Robust standard errors are reported inparentheses. ∗ 𝑝𝑝 < 0.05, ∗∗ 𝑝𝑝 < 0.01, ∗∗∗ 𝑝𝑝 < 0.001.

21

5. Discussion
5.1. Summary of the findings
Our testing of 141 sample fertilizers shows that, on average, unbranded fertilizers in the
Mekong Delta region of Vietnam contain the nutrient content as labeled, but with wide variation.
Prices are negatively correlated with deviation rates, but are too noisy to serve as a signal of
quality. The results are consistent with the reports that farmers do not express strong concerns
about fertilizer quality, nor do they adjust fertilizer use accordingly (Kojin et al. 2023). This is incontrast to SSA, where farmers tend to (mis)perceive fertilizer quality as poor and apply
inadequate amounts (Michelson et al. 2021).
We sought to investigate the sources of the compositional variation. We find that mixed
fertilizers have greater variability for the deviation rate of each nutrient as well as copositionalvariations between nutrients within a sample. Interestingly, nitrogen tends to mask the phosphate
deficiency.
5.2. Generalizability and sampling issue
Our results may overstate the quality variation and low quality fertilizers in Vietnam because
our purposive sampling focused on the high-risk market segment of low quality fertilizers. We
sampled only from certified fertilizer retailers. The extent of uncertified retailers is unknown, but
by definition, these stores are not allowed to sell the products. Since retailers are regularly
inspected, it is likely that unlicensed stores are the exception. The major brands, which we
intentionally excluded from our sample, are likely to be of more stable quality with little deviationfrom the label because they are regularly inspected to renew their production and distribution
licenses and voluntarily provide quality guarantees (Kojin et al. 2023). In addition to the major
brands, new brands are also mushrooming all over the market, and are sold at lower prices toattract customers.
Our analysis shows that the quality of these cheap, unbranded products is decent on average,
but with non-negligible variation, possibly indicating the inability of producers to control quality.
An important implication is that, despite the large heterogeneity across samples, average quality
is driven by regulation rather than reputation, because our samples are unbranded. This
underscores the importance of public regulation in the governance of the markets for experience
goods (see Section 2.1).

22

The weak correlation between price and quality may be due to sample selection bias, as we
intentionally selected the cheapest fertilizer product in each retailer. However, since we find thatthe mean deviation rates are close to zero, even for these purposefully selected samples, it is likelythat price-quality correlations will not be strong when we include branded fertilizer products.
A limitation of our sampling strategy is that we did not uncover direct sales by small
producers, 16 including newly established ones, who are likely to have received fewer inspections
and have less production knowledge and technology. This will understate the overall picture of
the fertilizer quality problem, but we believe that this channel is not large enough to invalidate
our conclusion. However, further studies are needed to clarify the situation in this channel.
5.3. Comparison with other studies
The situation in Vietnam contrasts with SSA, where farmers tend to (mis)perceive fertilizer
quality as poor and apply inadequate amounts. We find that 49% of the samples in Vietnam areout of compliance for any of nitrogen, phosphate, or potassium, containing less than 90% of thelabeled nutrient level, and the non-compliance rate for nitrogen is 14%. In contrast, Michelson etal. (2021) found that 23% (146 out of 633) of samples from agro-dealers in Tanzania were out ofcompliance (containing less nutrients than the legal standard) for nitrogen. What surprises us is
the low deviation rate in Tanzania, which has not established adequate regulatory systems(Michelson et al. 2021). However, as we suggest in this study, we may be able to learn more about
the low-quality fertilizer problem and draw policy implications by looking at compliance rates
for the three major nutrients rather than focusing solely on nitrogen.
Although more research is needed to make a more comprehensive international comparison of
the extent of the problem, we believe that the situation in Vietnam is settling down. As wediscussed in section 2.2, there are public and market initiatives underway to manage fertilizer
quality. It is possible that these initiatives will be effective in mitigating the problem.
5.4. Over-concentration of nitrogen
The over-concentration of nitrogen (mean deviation rate of +3%) needs some discussion. It is
not clear why this occurs. Possibilities include mislabeling, inadequate technology

16

Large producers are more likely to rely on their distribution channels (Figure 1) and avoid thehigh transaction costs of selling directly to farmers.
23

(manufacturing defects), and deliberate addition of nutrients. There are potential incentives for
manufacturers to over-concentrate nitrogen to stimulate crop growth and to impress farmers thatthe product is of better quality than others (suggested by a fertilizer expert). While the magnitudeof over-concentration is small, overuse of nitrogen in general can cause soil acidification, waterpollution (eutrophication), and air pollution through the emission of greenhouse gases such as
nitrous oxide (Cassou 2018).
5.5. Causes of compositional variations
Given our small sample size, we were unable to draw firm conclusions on the causes ofcompositional variation. We found a consistent pattern of variation in deviation rates that would
be predicted by inadvertent technical problems due to poor stirring during production. Taken
together with the evidence that mixed fertilizers had a higher deviation rate than complex
fertilizers, and that mixed fertilizers do not require high technology to produce, selection for lowskilled manufacturers to produce mixed fertilizers may be a leading explanation for the cause ofcompositional variation.
Another possibility is intentional deviation by profit-maximizing and dishonest fertilizer
manufacturers, who reduce costly nutrients and increase less costly nutrients instead. The
observed compositional variations show that nitrogen is being enriched while phosphate is being
diluted. The most recent USDA survey of fertilizer prices shows that phosphate is more expensive
than nitrogen and potassium (USDA 2019). 17 In addition, potassium is particularly expensive or
difficult to source for fertilizer producers in Vietnam. According to our interview with a large
fertilizer producer in August 2019, they procured all materials from their group companies, except
for potassium, which they imported (see also Bui (2019)). Thus, the observed pattern is consistent
with profitable deviation, where producers use cheaper nitrogen instead of potassium.

6. Conclusion
To investigate fertilizer quality in Vietnam, we tested the nutrient content of 141 fertilizer
samples in the Mekong Delta region. We deliberately sampled the unbranded products to focus
on the market segment where the low quality fertilizers are most likely to be found. We found17

The price of urea containing 44-46% of nitrogen was 571 dollars per ton as of 2014, the priceof super-phosphate containing 44-46% of phosphate was 621 dollars per ton, and the price ofpotassium chloride containing 60% of potassium was 601 dollars per ton (USDA 2019).
24

that, on average, the fertilizers contain the nutrient content as labeled. However, there are large
variations between samples. Half of the samples did not meet the legal requirements for at least
one of the three main nutrients and 21% of the samples are identified as substandard based on theaggregate deviation rates. In 6% of the samples, all three nutrients were below the labeled levels.
In addition, some fertilizers have too much of some nutrients and too little of others.
The results suggest that the quality of unbranded fertilizers in Vietnam is reliable in the sensethat labels can be trusted, but we cannot rule out the possibility of simple adulteration by adding
contaminants or mislabeling. The presence of large variations in quality suggests that there isroom for improvement in stabilizing quality. In addition, the finding that nitrogen is overconcentrated on average, may warrant policy attention, as farmers may inadvertently over-apply
nitrogen and harm the environment.
Due to our targeted sampling focus on unbranded products, further investigation of thesegments that were excluded from our study is needed to fully uncover fertilizer quality in
Vietnam. Sampling from large producers, which account for most of the market share and which
we assumed to have a near-zero deviation rate with low variability, and direct sales from local
small and medium producers, which are concerned about low quality, are the remaining segments.
Identifying the causes of quality variation is important to guide policy implications. We havealso focused on only a few specific potential causes of quality variation. Further understanding of
the production process, cost structures, and incentives for producers to reduce or over-concentrateindividual nutrients, as well as technical difficulties and problems, will narrow down a more
rigorous and specific hypothesis.
Finally, a fundamental question is when and how regulation or reputation can govern themarket for the experience goods. Our results suggest that regulation is important in our context
because our samples are unbranded and have no reputation. Future studies could also examine
policies that induce and support market initiatives under limited administrative capacity, typicallyin developing countries. Frequent inspections, their announcement, and third-party quality testing
services (Saenger et al., 2014) are potential candidates for such policies.

25References
Newspaper
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