125B The Politics of Food in a Global Economy (Naoi)
Template for Assignment I. Keep the roman numeral formatting (I, II, III-A, etc) and
section titles below. I also describe the detailed steps to complete this assignment below.
I. Research Design
Justify, in two sentences or less, why you chose the two countries that you chose. Are
their levels of economic development (measured by GDP per capita), region (Africa,
Asia, Latin America etc) or political institutions (democracy vs. autocracy, types of
electoral systems) similar? Alternatively, you can randomly choose two countries. If this
is the case, briefly describe your randomization methods.
II. The Patterns of Agricultural Protectionism
This section should be one figure and one paragraph.
Figure 1 should be a line figure, where the X-axis is year, and the Y-axis is the levels
of agricultural protectionism (measured by nominal rates of assistance, NRA) in the
two countries. Follow a guideline on how to visualize the data below (captions, legends and
source information). Follow the example below (legends, titles and captions).
Then briefly describe the patterns found in the figure. First, describe cross-national differences
(i.e., which country has higher level of protection than the other, do these governments subsidize
or tax farmers etc.). Second, describe trends (i.e., over time changes—increase vs. decrease) and
note around what year(s) sharp changes, if there are any, occurred.
III. Explaining the Cross-national & Temporal Patterns in the Agricultural Protection
This section summarizes your research findings on the determinants of agricultural
protection in the two countries of your choice. You must engage two approaches: the
logic of collective action and political institutions. First, summarize your main findings
on which approach explains the outcome better in a few sentences.
A. The Logic of Collective Action (one page)
This section summarizes your research findings on the political power of farmers
relative to consumers in the two countries. What proportion of the labor force
engages in agriculture, and what proportion engages in manufacturing or service
sectors? Which of the two countries does the logic of collective action (Olson 1965) predict
farmers to have a larger influence (hence higher NRA) than the other? Is this prediction
consistent with the data presented in Figure 1?
In addition to the proportion of labor force, briefly discuss whether farmers are strongly
organized (e.g., high organization rates of Agricultural Cooperatives, organize revolt, or support
particular political party?) and active during elections (endorsing candidates, mobilizing votes
etc)? If not, are consumers strongly organized (e.g., organize protests and food riots, or, vote
against incumbents when food prices are high?) in these countries?
You must use the following sources (& feel free to go beyond them): (1) World
Development Indicators (“WDI”) at World Bank (look for “% employment in agriculture”), (2)
articles from Google scholar (possible key words: country name & Agricultural
Cooperative & election. Other things being equal, go for scholarly works with higher
number of citations and more up-to-date) and (3) Factiva (go to UCSD library
website and type in “factiva” under search—it’s a newspaper aggregation database).
B. Political Institutions (one to two pages)
This section summarizes your research findings on the characteristics of political
institutions in the two countries. This summary should include: their regime type (democracy or
autocracy) and electoral systems (only if they are democracies), and whether there were
important changes in political institutions (e.g., democratization or electoral reform) and when.
your expectation about how these political institutions affect the levels of agricultural protection.
Then discuss whether the actual patterns of protectionism described in Figure 1 conform to the
expectations or not.
You must use the following sources (& feel free to go beyond them): (1) Polity IV data
(http://www.systemicpeace.org/polityproject.html, also see my lecture slides on this data), (2) for
electoral systems, Data on Electoral Systems Worldwide (http://www.idea.int/esd/world.cfm),
(3) scholarly articles you find in Google scholar (possible key words: “electoral system &
farmers & country name” or “electoral reform & farmers & country name”. Try other
combinations of key words, and if (3) does not hit much information, then, (4) Factiva (go to
UCSD library website and type in “factiva” under search—it’s a newspaper aggregation
database).
IV. Your own mini-research (one to two pages which can include figures and/or tables)
This section summarizes your findings on other possible factors affecting the pattern
of protectionism. You can just focus on one alternative factor that might affect the
pattern.
Some possibilities: external economic shocks (commodity or oil booms), multilateral
or bilateral trade agreements (e.g., negotiation rounds at World Trade Organization, trade
agreements with big agricultural exporters), trade reforms (“unilateral liberalization”) or cultural
factors. If necessary, you can see the level of protection (“Nominal Rates of
Assistance” or other measures) broken down by commodities.
V. Bibliography (No need to count this section toward 5-page limit)
Note on Citations: Use in-text citations throughout and use bibliography at the end for
any readings/materials that are not on the syllabus. If you are citing from the required readings,
(AUTHOR YEAR) is sufficient, such as (Olson 1965) and (Rogowski and Kayser 2002) and no
need to have a full citation in the separate bibliography section.
MLA or APA style as long as they are consistent. If you are citing from my lecture, use (L) as intext citation.
Newspaper articles from Factiva
APA
Simon, R. & Hagerty, R. (2005, September 29). Mortgage lenders tighten standards;
Amid concern over risk, banks make it harder to qualify for certain home loans. Wall
Street Journal, D1. Retrieved October 4, 2005, from Factiva database.
MLA
Simon, Ruth, and James. R. Hagerty. “Mortgage Lenders Tighten Standards; Amid
Concern Over Risk, Banks Make It Harder to Qualify for Certain Home Loans.” Wall
Street Journal 29 Sep. 2005: D1. Factiva. Web. 4 Oct. 2005.
Newspaper articles on-line (from the newspaper company’s website)
APA
Last, F. M. (Year, Month Date Published). Article title. Newspaper Title, pp. Page(s).
Retrieved from URL.
Example:
Bowman, L. (1990, March 7). Bills target Lake Erie mussels. The Pittsburgh Press, p.
A4. Retrieved from http://www.pittsburghpress.com
MLA
Last, First M. “Article Title.” Newspaper Title Date Month Year Published: Page(s).
Website Title. Web. Date Month Year Accessed.
Example:
Mushnick, Phil. “Sterling Continues to Call it Wrong.” New York Post N.p., 23 Apr.
2012. Web. 2 Jan. 2013.
Citing Information on Websites:
APA: Consult this website http://www.bibme.org/citation-guide/apa/website
MLA: Consult this website http://www.easybib.com/reference/guide/mla/website
Step-by-Step Guide to Assignment I
Step 1: Download the Data & Note
Citation for this Dataset: Kym Anderson and Signe Nelgen, “Updated National and Global
Estimates of Distortions to Agricultural Incentives, 1955 to 2011”, Washington, D.C., June 2013.
(Available at www.worldbank.org/agdistortions website)
Try this URL:
http://econ.worldbank.org/WBSITE/EXTERNAL/EXTDEC/EXTRESEARCH/EXTPROGRAM
S/EXTTRADERESEARCH/0,,contentMDK:21012395~pagePK:64168182~piPK:64168060~the
SitePK:544849,00.html
(On the above page, click the tab “Database” and Download 2011 version)
Alternatively, try this link:
http://econ.worldbank.org/WBSITE/EXTERNAL/EXTDEC/EXTRESEARCH/0,,contentMDK:2
1960058~pagePK:64214825~piPK:64214943~theSitePK:469382,00.html
Scroll down the above website and click: “Core database (updated to 2011)”. You will be using
this data for the Assignment I.
If neither works, then, google for this data: Kym Anderson and Signe Nelgen, “Updated National
and Global Estimates of Distortions to Agricultural Incentives, 1955 to 2011”, Washington,
D.C., June 2013. (Available at www.worldbank.org/agdistortions website)
The link below will take you to regional and country-specific reports on agricultural
protectionism using the above data:
http://econ.worldbank.org/WBSITE/EXTERNAL/EXTDEC/EXTRESEARCH/EXTPROGRAM
S/EXTTRADERESEARCH/0,,contentMDK:21812190~pagePK:64168182~piPK:64168060~the
SitePK:544849,00.html
Also download “Note summarizing core updated database (Updated to 2011)”:
http://siteresources.worldbank.org/INTRES/Resources/469232-
1107449512766/Note_summarizing_core_updated_database_0613.pdf
In this “Note”, you will find a list of countries and commodities included in the dataset, as well
as a brief description of variables in the dataset.
Table 7 on page 18: Table 7: Variable names used in the Excel Spreadsheet in Anderson and
Nelgen (2012)
The variable named “NRA” is nominal rate of assistance for each product.
For Figure 1, we need an average NRA for each of the two countries. We want to use the
variable named “NRA_covt, ” which is a mean of NRA for products covered in the dataset (to be
precise, “NRA_covt” is a value of production-weighted average per country and year).
Step II: Choose two countries & make Figure 1.
To do so, you would want to start a new excel spread sheet. The original dataset looks like this:
2
Screen shot of original dataset. Always keep the original dataset unchanged.
You want to reshape the data to look like below to make Figure 1.
Keep the top row to indicate the variable name (so that you don’t forget)
3
“nra_covt_Argentina” is “nra_covt” data for Argentina. I changed the variable name
to “nra_covt_Argentina” so that we know this is “nra_covt” data (as opposed to say,
“nra_tott”). Likewise, “nra_covt_Colombia” is “nra_covt” for Colombia. I changed the
variable name to “nra_covt_Colombia” so that we know this is “nra_covt” data for
Colombia.
To reshape the data, first go to “Window” in excel screen, and click “unfreeze panes”.
Keep variables “year”, “country”, “prod2” and either “NRA_covt” and/or “NRA_tott”,
“pop total” “pop_agric” and “pop_nonagric” and delete the rest. Rename the dataset
(so that you don’t get confused with the original one) to something like
“125B_Assignment1_edit.xls”.
Then copy & paste data for the two countries of your choice to a new excel
spreadsheet. When you paste, choose “paste special” and click “values” (when
original dataset embeds mathematical formula, simple copy & paste would copy the
formula. We want to copy & paste numbers) . The dataset should like the one on
the previous page (with nra_covt_Argentina & nra_covt_Colombia). Make sure that
the first column has no variable name (such as “Year”). Leave it blank.
Select all the numbers in the thee columns starting from the second row (where
“Argentina” and “Columbia” are), and click “chart” and choose this:
.
Then a line graph will appear. Right-click this figure, and choose “Move Chart”. A
screen will appear, so name this chart (e.g., “Figure 1”). And the full-size figure will
appear. You will notice that x-axis (year) is bit clamped. Click x-axis, and choose
“scale” at the bottom. The following screen will appear. Change “Interval between
tick marks” to 5 (or play around with different numbers to see what looks best for
you).
4
Y-axis needs a title. To do this, click “tookbox” in excel (located at the top) and
choose “Vertical (Value) Axis” under “Titles” (see a vertical panel on right below).
They type in “Nominal Rate of Assistance”. Adjust fonts to your liking (12-14 fonts
are generally good).
5
Now, copy and paste (choose “paste special” and click “pdf”—that would make the
figure look cleaner) this figure to word document.
6
Add (1) Title of the figure, (2) Source information at the bottom (don’t forget to
include the access date—the date you accessed & downloaded the dataset), and (3)
Note at the bottom.
Figure 1: Nominal Rate of Assistance in Argentina and Colombia, 1960-2009
Source: Kym Anderson and Signe Nelgen, “Updated National and Global Estimates of
Distortions to Agricultural Incentives, 1955 to 2011”, Washington, D.C., June 2013.
(Available at www.worldbank.org/agdistortions website, last accessed Month Date,
Year).
Note: Nominal rate of assistance (NRA) used in this figure is value of productionweighted average of covered products (a variable named “nra_covt”) in the above
dataset.
DONE!
