A question I am always asked during open houses is about certifications. Do they matter in the job hunting process? Do they improve earnings? Unfortunately, these questions do not have a straightforward answer. Nevertheless, the Federal Reserve Bank of Dallas published a blog post that examines earnings and certifications. They investigate the certifications mentioned by employers in job ads and also examine the earnings differentials between workers with and without certifications. This analysis indicates that the decision of getting a certification should made on a casa by case basis.
A Suggestion for Teaching Econometrics and R Together
Besides choosing a useful textbook, an interesting aspect of teaching Applied Econometrics has been the choice of the software package. As a student, I had a hard time dealing with textbooks that were not integrated with the software used in homework problems. The issue was that I had to spend a lot of time finding other sources to learn more about the software. In hindsight, I think it was very inefficient. Anyway, I came across a very nice textbook of Applied Econometrics that is well integrated with R, and it includes some data and examples. This textbook is called “Applied Econometrics with R” by Christian Kleiber and Achim Zeileis. It also has a companion website with slides, handouts, and some R code that I find extremely useful.
New evidence on WTO membership after the Uruguay Round: an analysis at the sectoral level.
Magnus dos Reis (Unisinos), André Filipe Zago de Azevedo (CNPq), and I have a forthcoming paper at Open Economies Review that examines the effects of WTO membership on trade flows, with a special focus on sectoral trade flows. The full paper is available upon request.
Abstract
The creation of the World Trade Organization in 1995 brought several changes to the world trade system, including more stringent accession commitments, separate agreements for agricultural products and for textiles and garment. This study examines the effects of WTO membership on disaggregated sectoral trade flows and their extensive and intensive margins by means of a gravity model estimated by Poisson pseudo-maximum likelihood. We employ a panel dataset on bilateral imports for agriculture, textile, and manufacturing sectors for the 1995–2017 period. Our estimates suggest that WTO membership has succeeded in expanding trade flows for new members. Nevertheless, this growth occurred asymmetrically between developed and developing countries, and among the different types of products. In the period under review, developing countries benefited most from this WTO-promoted increase in world trade, in stark contrast to the findings of the extant literature for 1950–2000. The largest trade growth occurred in the agriculture sector, which is also at odds with earlier findings of growth in manufacturing products only. Furthermore, our results show that the increase in trade due to WTO liberalization took place exclusively in the extensive margin of trade, most of which also happened in the agricultural sector.
Data repositories
Open ended questions are usually difficult to answer, for instance where one can find data sources for economic indicators. Perhaps, the following list may suggest good places to start your quest for data.
Data Sources: A Compendium by the Econbrowser website
Data Sources at the American Economic Association website
Economic Data freely available online by the Economics Network
IMF Data by the International Monetary Fund
Public Use Data Archive by the NBER
Good luck in your data hunting!
Cheat Sheets for Stata
Cheat sheets for programming languages were commonplace before the internet became widely available with powerful search engines. Nowadays, I believe that cheat sheets are still very useful because search engines become simply too powerful and provide more answers than required by the question. Some of the most popular cheat sheets for Stata were prepared by Tim Essam and Laura Hughes from the US Agency for International Trade and Development. Follow them on twitter: @StataRGIS and @flaneuseks. Here are some of their cheat sheets:
Learning about Forecasting (and using R)
As I was designing an introductory course in forecasting for International Business students I came across a very interesting book available for download in the web. The book is “Forecasting: Principles and Practice” by Rob J Hyndman and George Athanasopoulos. Among several nice features, I would stress that this book is for (undergraduate and MBA) business students with little formal training in statistics and it presents plenty of examples using R. The third edition uses the tsibble and fable packages, while the second edition uses the forecast package. I really like chapters 2, 3, and 4 where the authors go over exploratory analysis of time series.
Free book about basic statistics with examples in R
An interesting book for those that are starting to learn basic statistics for data analysis is Practical Statistics for Data Scientists by Peter Bruce and Andrew Bruce. It can be downloaded for free here. This book covers the basics of data exploratory analysis and frequentist statistical theory. Additionally, its final chapters cover classification, statistical machine learning, and unsupervised learning. I do like these last chapters as they are carefully written and easy to understand. The examples using R are very useful. In sum, this is a book worth reading for beginners. The last chapters can also be very helpful for those readers with more experience in data analysys.
Learning the basics of Unix
Teaching computer skills to students has always been a challenge in Economics. The first difficulty is the limited amount of time for them to learn the basics of any software. A second difficulty is when the software is only available for Unix. Recently, I found a very simple yet comprehensive tutorial for the basics of Unix. Most of my students that used it were able to quickly gain some proficiency and write better code, especially when using bash.
An introductory book on econometrics using R
A major issue with introductory econometric textbooks is that they are either too theoretical or too practical. While the former does not motivate students, the latter provides training and not an education. It is very difficult to reach a compromise between these two types. Nevertheless, there is a book that was able to get a good balance between theory and applications using R. It is titled “Introduction to Econometrics with R” and written by Christoph Hanck, Martin Arnold, Alexander Gerber, and Martin Schmelzer. Most important, the examples and applications presented in the book are carefully chosen to illustrate the theoretical aspects that are being discussed. For those that already know basic econometrics, this book is still useful to learn a lot about R.
New Database on Trade Facilitation
The World Trade Organization (WTO) promoted the Agreement on Trade Facilitation (TFA) in order to foster international trade by simplifying cross-border trade procedures, which reduced not only transit time but also costs. When fully implemented, the TFA is expected to substantially reduce trade costs by 10%-18% (OECD, 2018 ) and at the same time to increase exports by more than 3 trillion dollars per year (WTO, 2015).
UNCTAD just released a real-time database that comprises standardized data from national trade facilitation committees (NTFCs). This allows scholars and practitioners to follow and study the implementation of the commitments made by each country under the TFA agreement. The video below provides more details on this interesting and promising database.
Labor Provisions in Trade Agreements
A very important question for those concerned with job precarization is whether and how this phenomenon is impacted by globalization and more specifically by international trade. A key hurdle has been the absence of a well organized dataset of the labor provisions included in trade agreements. This would allow not only for a cleaner identification of the effects of trade but also for an estimation of the impact of the labor provisions. Fortunately, the International Labour Organization recently made available a dataset of this type. It covers more than 100 trade agreements and 140 countries! You can find more about the typology used here, about the dataset here, and in the video below.
A comprehensive road map to learn R
Learning a new software or even a new programming language is always an interesting journey. Most of the times the tutorials and books we find are never exactly what we need. A useful resource that I found is the Big Book of R. It is one of the most comprehensive repositories of tutorials and general information about R. You can find suggestions according to your needs or even according to your background, for instance for Journalism, Social Sciences, or Life Sciences. It has very good sections on Machine Learning and on R programming.
Nesting local macros in Stata
Local macros are a very useful feature of Stata. Here is a simple example.
local macro1 “Hello!”
local macro2 = “How are you?”
local macro3 2+2
local macro4 = 2+2
di ” `macro1'`macro2′ ”
di “Here’s some math: `macro3' = `macro4′ ”
A few comments are in order here. macro1′ tells Stata to replace this expression with the contents of the local macro1. Make sure to leave no spaces inside the `’. Also, note how macro3 and macro4 lead to different outcomes. You need to use the equal sign to make Stata to evaluate the expression, otherwise it will treat it like a string.
Now, Stata applies the “parentheses rule” when replacing local macros for their contents. That is, it first replaces the innermost local macro, then the second innermost local macro, and so on. Here is an example.
local macro5 “nest”
local nestmacro “Local macros can be nested!”
di ” “macro5’macro’ ”
Let’s add another layer to the nesting of the previous example and play with it a little bit more:
local macro5 “nest”
local macro6 “macro”
local macro7 5
local nestmacro “Local macros can be nested!”
di ” “macro`macro7”`macro6” ”
I guess you have a pretty good idea of how this works now. Good luck in your Stata coding.
An Introduction to Statistical Learning with Applications in Python
I came across this very interesting Github repository by Qiuping X., in which she posted the codes she prepared in Python for the book “An Introduction to Statistical Learning with Applications in R” by Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani. This is very useful for those that are learning Python and certainly facilitates the migration from R to Python too.
A little bit more about loops and macros in Stata
Loops and lists are important tools for Stata programmers. Although these tools may not be the most computationally efficient technique, they can be of great help during the early stages of code development. By the way, it is always good to keep in mind that a good programming practice is to always keep definitions local to the do-file you are coding whenever possible.
The first example is about using a counter. You can place it on the do-file editor and then run it.
local fruits apple banana pear
local counter 0
foreach d of local fruits{
local counter= `counter’+1
display “ `counter’ – `d’”
}
After running it, the output should be something like this:
1 – apple
2 – banana
3 – pear
Notice that I used the equal sign “=” to build the counter. In short, you have to use it. Just for fun, see what happens when you replace “local counter= `counter’+1” by “local counter `counter’+1”.
Now suppose we have an ordered list of produce 4-digit codes and we would like to display the PLU code next to each fruit name.
local fruits apple banana pear
local plucode 3009 4011 4414
/* The first step is to find out the number of fruits */
local fruitnumber: word count `fruits’
di “Fruit – PLU code”
/* The second step is to build a loop to pair each fruit with its PLU code */
forvalues j = 1/`fruitnumber’ {
/* The third step is to pick the j-th element of each list to have them paired */
local pair1: word `j’ of `fruits’
local pair2: word `j’ of `plucode’
display “`pair1′ – `pair2′”
}
Output:
. local fruits apple banana pear
. local plucode 3009 4011 4414
. /* The first step is to find out the number of fruits */
. local fruitnumber: word count `fruits’
. di “Fruit – PLU code”
Fruit – PLU code
.
. /* The second step is to build a loop to pair each fruit with its PLU code */
. forvalues j = 1/`fruitnumber’ {
/* The third step is to pick the j-th element of each list to have them paired */
local pair1: word `j’ of `fruits’
local pair2: word `j’ of `plucode’
display “`pair1′ – `pair2′”
}
apple – 3009
banana – 4011
pear – 4414
.
end of do-file
So, the “word count” function returns the number of elements of the macro. And the “word `j’ of `fruits’” returns the j-th element of the macro fruits. You can find more about these macro extended functions on Stata by typing “help extended_fcn”.
EU and Brexit
The bulk of the negotiations regarding the United Kingdom withdrawal from the European Union were concluded on December 24, 2020. The details are available here: https://ec.europa.eu/commission/presscorner/detail/en/ip_20_2531 .At a first glance, this seems to be a reasonable agreement that avoids most of the doomsday scenarios portrayed by many observers. Although there are several details to be worked on, the most important aspect of this agreement, in my opinion, is the creation of a Free Trade Area between the UK and the EU. This FTA should pose little friction on trade flows, unless significant red tape is created. An interesting question is whether this FTA agreement with the EU will facilitate or hamper the other trade agreements that are being negotiated by the UK.
Inflation Targeting
Inflation targeting is a somewhat new approach to the role of Central Banks. This system was implemented in Brazil when I was a senior in college. I still remember the debate on whether inflation targeting was appropriate to a developing country like Brazil and most analysts predicted it wouldn’t last long. That said, inflation targeting has been used for approximately 20 years in Brazil.
There is a book about inflation targeting written by Pierre-Richard Agénor (University of Manchester) and by Luiz Pereira da Silva (BIS). This book is titled “Integrated inflation targeting: Another perspective from the developing world”. It provides a wealth of information about recent experiences with inflation targeting in developing countries, including discussions about how it performed in light of the global financial crisis and the issues faced by policymakers. This is a very nice manuscript and I strongly recommend to those interested in learning more about inflation targeting.
The infancy of Mercosul (or Mercosur)
There are two very interesting books in pdf format about Mercosur by Paulo Roberto Almeida that can be downloaded for free.
The first book is titled “O Mercosul no Contexto Regional e Internacional ” (Edições Aduaneiras, 1993). It provides some background information about the foreign affairs in the Southern Cone of South America. And it goes over the fundamentals of the Mercosur. This book was written between the conclusion of the main negotiations of Mercosur and the implementation of the Mercosur. Thus, it provides an interesting perspective on the crucial issues and expected impacts of Mercosur, see for instance chapter 10.
The second book was published in 1998, three years after the the implementation of Mercosur. It is titled “Mercosul: Fundamentos e Perspectivas” (São Paulo: Editora LTr, 1998, 160 p.; ISBN: 85-7322-548-3). This book puts the Mercosur in the context of the century-old idea of Latin American Integration. Also, it goes over the implementation of the Mercosur and the first issues experienced by the member countries. Finally, in chapter 9, the author discusses the relationship between Mercosur and the (now defunct) FTAA-Free Trade Area of the Americas.
I strongly recommend these two books for scholars interested in learning more about the ambitious albeit problematic integration agreement that is the Mercosur (or Mercosul…).
Statistical Learning using R
I recently came across this book titled “An Introduction to Statistical Learning, with Applications in R“.
It can be downloaded for free at the authors webpage, which also contain the R codes, data sets, errata, slides and videos for Statistical Learning MOOC, and other valuable information.
That said, I think this is a very useful book for those interested in Statistical Learning. It is very accessible to most people, since it does not require a strong mathematical background.
For those interested in gaining a deeper understanding of these topics, I strongly suggest the book “The Elements of Statistical Learning“, which is also available for download at no cost.
Stata tip: creating a local containing all (or almost all) variables of the data set
Locals containing a list of variables can be very useful when using Stata. A common need is a local containing all variables of a data set. This local can be created by means of the ds command.
Here is an example using the lifeexp.dta data file.
. webuse lifeexp, clear
(Life expectancy, 1998)
Now, let’s create a local named allvar that will contain all variables of this data set.
. ds
region country popgrowth lexp gnppc safewater
. local allvar `r(varlist)’
. di “`allvar'”
region country popgrowth lexp gnppc safewater
We can see that ds stored the variable list into r(varlist). One interesting variation is the creation of a local containing all variables except region. You will need to specify the variables to be escluded right after ds, and add the option not after a comma.
. ds region, not
country popgrowth lexp gnppc safewater
. local othervar `r(varlist)’
. di “`othervar'”
country popgrowth lexp gnppc safewater
The command ds has several other useful applications that will be commented later in this blog.
The erratic Brazilian trade policy
The recent elections in South America indicate a major change in course for the Southern Cone countries and also for Bolivia. This change is not uniform across countries, and in some cases can be in opposite directions like the cases of Brazil and Argentina. Interestingly, the Brazilian trade policy experienced large changes over time, in part due to balance of payments constraints. Since the 2000s, Brazil did not pay much attention to Mercosur because of its large trade surpluses from the China-induced commodity boom. Nevertheless, the current government in Brazil sees Mercosur as a stumbling block to trade negotiations with other countries. The fundamental question is what are the goals of the current Brazilian trade policy? A key ingredient of any answer to this question is contained in an interesting article by Paulo Roberto Almeida that revisits the history of the Brazilian trade policy. This is a very nice and succinct paper that I recommend to everybody interested in learning more about Brazilian trade policy.
Some resources for using R with spatial data
Spatial data models and visualizations are important tools in the design of public policies. I provide below some links to tutorials about spatial modelling using R that I have found useful.
The first stop should be at the Spatial Data Science with R website. It contains a wealth of information organized in a straightforward way. My next suggestion is An Introduction to Spatial Econometrics in R website. A different version of the previous website is also available at R-Bloggers: An Introduction to Spatial Econometrics in R. There is also a tutorial by Luc Anselin: An Introduction to Spatial Regression Analysis in R.
Finally, there is a video made by econometricsacademy about Spatial Econometrics in R.
The past of Mercosur (or Mercosul)
The recent presidential elections in South America have raised concerns about the future of Mercosur, or Mercosul for Portuguese speakers. Although it is too early to make any reasonable prediction, it is interesting to note that Mercosur since its inception has been always more than just a trade agreement. This point has been overlooked by many analysts. And perhaps, this is the reason behind the survival of this agreement. An excellent starting point for those interested in learning more about Mercosur is a paper by Paulo Roberto Almeida titled “Regional Integration in Latin America: Historical Developments, Current Challenges, Especially in Mercosur”. This nice paper examines the evolution of the Southern Cone countries’ foreign policies since the early eighties. It goes over the foundation of the Mercosur in 1991 and the conflicts between member countries that that have taken place after 1999.
Transferring IPEADATA series to Stata
A common issue that arises when converting time series data from IPEADATA to Stata format is dealing appropriately with the time variable. For instance, for monthly series the date format will be YYYY.MM. Stata usually interprets this format as numeric.
Suppose you already downloaded a monthly series from IPEADATA and transferred it to Stata. It is very likely that the date variable (let’s call it date) has been automatically handled as a numeric variable. The first thing to pay attention is that the numeric format disregards zeroes on the right-hand side of the decimal point. This means that October of 1940 is coded as 1940.10 by IPEADATA and interpreted as 1940.1 by Stata. To recover the missing zero, the first step is to convert this variable to string format. This can be done with the string() function.
generate sdate=string(date)
To add back the missing zeroes, we can do the following:
replace sdate=sdate+”0″ if length(sdate)<7
Now, we just need to tell Stata to interpret sdate as a monthly date variable. This can be accomplished with the command numdate. This is not a standard Stata command and needs to be installed in your computer (ssc install numdate).
numdate mo newdate = sdate, pattern(YM)
The above line can be interpreted as create a new date variable named newdate from variable sdate that is in the YYYY.MM format.
The numdate ado file can deal with very flexible date specifications, and its help file is very comprehensive. Two other useful commands are convdate and extrdate. They are used to convert or extract parts of dates from variables that are already in the Stata date format.
A final recommendation is to take a look at Stata documentation on dates that is available at http://www.stata.com/manuals13/ddatetime.pdf.
Labeling curves in Mathematica
Here is another quick tip about plotting curves using Mathematica. The option PlotLables can be used to identify curves. In our first example there are two curves named curve1 and curve2.
a = Plot[x+7, {x, 0, 12}, PlotLabels->Placed[{“curve1”}, Above]]
b = Plot[1.4*x, {x, 0, 12}, PlotLabels->Placed[{“curve2”}, Below]]
Show[a,b]
The result is disappointing. We cannot see the label of the second curve. This is so because the option Below places the label at the left end of the curve, which is not showing.
To fix this, use the options PlotRange and Exclusions:
Show[a, b, Exclusions -> None, PlotRange -> All]
A few tips for programming in Stata
Stata is a very powerful and useful statistical software. Just like any sophisticated tool, it takes time to learn about it. And you need to invest some time to master it. Programming is one of those skills that knowing a little bit can be very beneficial. Below you will find four videos. The first video goes over the functionalities of the Stata Program Editor. The second video covers some basics of Stata commands. The third video talks about loops, which are an essential tool for programmers. Finally, the fourth video is about macros, which together with loops are very useful to handle repetitive tasks.
How to use the Stata Program editor:
Basics of Stata:
Quick guide to loops:
More about macros:
How to plot step functions in Mathematica
Those interested in representing graphically the Relative Supply (RS) curve of a simple 2 x 2 Ricardian model of international trade in Mathematica will find that this task requires the use of Plot[] and Piecewise[]. Below you can find an example to illustrate this:
Plot[{Piecewise[{{0,x<=0},{1.5,0<x<1}, {2,x>= 1}}]},{x,0,12},Exclusions->None, PlotStyle->{Thickness[0.01]}, Axes->True,AxesOrigin->{0,0}]
Each portion of the curve is defined in Piecewise as {function, range}. So Piecewise[{15, x<=5}, {3x, x>5}] is for a function that takes the value 15 if x is smaller than or equal to 5 and the value 3x if x is greater than 5. Note also that in the example above I utilized several options of the command Plot[]. You can find more information about these options at https://reference.wolfram.com/language/tutorial/Options.html .
How to plot curves with different domains in Mathematica
Mathematica (or the Wolfram language) is a very useful tool to plot functions. Suppose you are interested in plotting two curves in the same diagram, let’s say y = 1/x and z = 2/x. Both functions have the same domain of x belonging to the [0,10] interval. This is easily accomplished by typing:
Plot[{1/x, 2/x}, {x, 0, 10}]
Suppose now that you would like to plot in the same diagram both functions but the domain of z change to x belonging to the [2,12] interval. How could you do this? This is not difficult. You just need to use the command show with the option PlotRange->All. Here is a piece of code that accomplish this:
p1 = Plot[{1/x}, {x, 0, 10}]
p2 = Plot[{2/x}, {x, 2, 11}]
Show[p1, p2, PlotRange->All]
Exporting Stata’s correlation tables to a document file
I came across a very useful ado file for Stata named asdoc that facilitates the creation of neat tables.
To install asdoc, just type ssc install asdoc .
Here is an example of exporting a correlation table to a document named table.doc.
sysuse auto
asdoc correl price mpg headroom trunk weight, save(table.doc) dec(3)
Note that dec(3) means to export the correlations with 3 decimal places.
Asdoc has tons of other applications. Its help file is very comprehensive. And you can have a glimpse of its capabilities in the following videos:
Harrod, Domar and the History of Development Economics
One of my recollections of the development economics course I took when I was a business school major was about the “Harrod-Domar model” in an undergraduate course about. I was amazed by the idea that government could foster economic growth. Yes, I was young and naive. Anyway, for those interested in the history of development economics I strongly recommend Dr. Mauro Boianovsky’s paper titled “Beyond capital fundamentalism: Harrod, Domar and the history of development economics” that was published in the Cambridge Journal of Economics. This amazing paper received the 2019 best paper award by the European Society for the History of Economic Thought. I hope you enjoy reading it as much as I did.
A nice tutorial for those interested in learning the basics of Python and its applications to Finance
The website called FinaceandPython has a very good tutorial on the basics of Python and its applications to Finance, Statistics, and Economics. This tutorial is organized in lessons that are carefully designed for a step-by-step learning experience. It also has several problem sets that will allow students to practice the concepts developed in the lessons. A key differential of this website are the examples and applications of Python coding to Finance problems. In sum, this is a fine tutorial for those interested in learning Python.
Social Security Reform in Brazil
Since I was a little kid Social Security reform has been discussed in Brazil. It is fair to say that in the early 1980s a huge actuarial deficit was already in place. Since the financial side was still fine, i.e. Social Security contribution revenues were larger than the paid benefits. Additionally, the hyperinflation of this period facilitated financial adjustments. All that was needed to balance the Social Security budget was to adjust benefits by less than the actual inflation rate.
To make matters worse, several significant changes affected the Brazilian economy since the late 1980s. First, the Brazilian Constitution of 1988 changed several Social Security rules for both private sector and public sector workers. These changes, among other nefarious effects, increased substantially the benefits paid without an increase in the contributions. Moreover, the Brazilian Social Security system is a pay-as-you-go system, which makes it very vulnerable to demographic changes. In fact, the fertility rate started to decline rapidly and at the same time life expectancy in Brazil increased considerably since the 1980s. Finally, the end of hyperinflation after the implementation of the Real Plan in July 1994 prevented the use of inflation by government to curb Social Security deficits. As a result, by the end of the 1990s, Social Security had both actuarial and financial deficits.
Several mild reforms have taken place since the mid-1990s, though none of them were able to restrain the ever increasing financial deficit. A new reform is currently being discussed in the Brazilian Congress. It is not clear, at least to me, whether it will be modified (and how) or even if it will be approved by Congress. In this link you can find some of the fiscal forecasts that were used to support the current proposal to reform Social Security.
Reading DATASUS and ANS .dbc files using R
Those interested in conducting research using Brazilian data often come across some unusual file formats used by Brazilian government agencies. One example is the .dbc files used for health data produced by DATASUS and by ANS. These .dbc files are not related to the.dbf files used by FoxPro for instance. In fact, they are just compressed .dbf files.
There is a package in R that can convert these .dbc files into regular .dbf files. This package is named read.dbc. Once you generated the .dbf files, you can use the package foreign and its function read.dbf to import the data into R. This very same package allow you to save the data using Stata .dta format by means of the function write.dta.
The package maptools also has a function to read dbf files named dbf.read, though I have not tried it yet.
New book about the Brazilian economy
The International Monetary Fund published a new book about the Brazilian economy. It first provides an overview of the Brazilian economy, and then cover the following important topics: Economic Growth, Social Progress, Fiscal Framework, Challenges to the Monetary and Financial Framework, and Fighting Corruption. This book can be downloaded for free here.
The third chapter (Current Constraints on Growth) is of interest for those trying to understand some of the reasons for the poor performance of productivity growth in Brazil, which many observers suggest to be the key structural problem of the Brazilian economy.
Machine Learning using Matlab
Economists in general do not consider Matlab their preferred choice of software. In part this is due to Matlab’s peculiar licencing scheme for its toolboxes. That said, for some applications, it is still a very useful piece of software.
Those interested in Machine Learning would certainly be interested in this new Matlab’s e-book. It is a basic tutorial on ML using Matlab. To download this e-book you need to go to this website and fill out a form, which will probably reduce your interest in using Matlab.
Third Worldism
Scholars interested in economic development are usually asked about policy recommendations to improve the standard of living the populations living in poor countries. This is an easy and at the same time a difficult question to answer. It is easy because the economic and the development scholarly literature has amassed a large amount of evidence regarding development policy effectiveness. And the scholar just needs to suggest some of these policies, for instance improving the quality of basic education. The difficulty of this question is if those individual policies work together (see the theory of the second best) and whether there is a political consensus that will allow the implementation of such policies.
This political consensus by its turn depends on the perceived causes of underdevelopment (colonialism, small capital stock, illiteracy, declining terms of trade, and so forth), on the political capital of each segment of the society, and on the goals to be achieved by development policies. Since the political consensus is multi-faceted and perhaps cumbersome problem, scholars and policy-makers approach conceptually it through the use of paradigms, in which scholars model the not only the entire economy and society of a developing country but also its economic and political relationship with the rest of the world. In this normative analysis, scholars end up choosing the winners and the losers of the proposed development policies according to the scholars’ values and beliefs.
One of these paradigms is the Third Worldism, which was very influential in the 1960s and 1970s. Fred Siegel (Manhattan Institute) wrote a very interesting piece about some of the key people related to the Third Worldism movements and its ramifications. I urge interested readers to read Fred Siegel’s article.
Book on Linear Algebra with applications in Julia
I came across this very interesting book titled “Introduction to Applied Linear Algebra – Vectors, Matrices, and Least Squares” by
Stephen Boyd and Lieven Vandenberghe and published by Cambridge University Press.
On the book’s website you can find a pdf file of the book for download. You can also purchase it at a (virtual) bookstore.
Additionally, you can find there more exercises and a Julia language companion.
I think this is a great book and the companion materials are very helpful. I strongly recommend those interested in learning Julia to go over the companion material.
Tutorials for learning Julia
The Julia Language webpage contains a page with several tutorials.
I recommend the following video tutorial:
Julia: a powerful computer language
Julia is a programming language that should be of interest for those dealing with big data. Many observers claim that it was developed with the primary goal of high performance. And it is free for everybody to use. You can find its source code on GitHub.
You can download Julia and find its official documentation at the Julia Programming Language webpage.
Roberto Campos and the Brazilian Constitution of 1988
Let me talk again about Roberto Campos and the Brazilian institutions. After a heterodox economic plan was implemented in February of 1986, the entire country was happy and enthusiastic. Later in the year, Brazilians voted for state governor and for a new Congress. Most important, the elected members of this new Congress were also in charge of writing a new Constitution for Brazil. Campos was elected deputado federal (a representative in the Brazilian lower chamber).
As I mentioned in a previous post, he was involved with many of the institutional changes that took place in Brazil between 1964 and 1967, including the creation of the Brazilian Central Bank. Unfortunately, his role in the drafting of the new constitution would be a much smaller one. Although many observers claim that the 1988 Constitution represented a move forward in civil and political rights, the majority of the economists believes that it severely reduced the economic freedom in Brazil by given the Brazilian federal government a central role in the country’s economy.
With a tad of melancholy, Roberto Campos produced several essays about the changes introduced by the 1988 Constitution that were made available in a book titled “A Constituição Contra o Brasil” (The Constitution against Brazil). This book is a must read for those trying to understand the (good or bad) changes introduced in the Brazilian economy after 1988. A pdf of the book (in Portuguese) is available here.
Tutorials for learning Tableau
Some students asked me about a tutorial to learn the basics of Tableau.
Although there are many tutorials available, I found the following videos to be the most straightforward ones.
More specifically, for those wanting to learn how to create a dashboard in Tableau, I recommend the following tutorial:
A good tutorial for learning the basics of Python for data analysis
I founds this interesting tutorial for Python. In my opinion, Python is a very simple and intuitive language, and at the same time it is very powerful. This link leads to a straightforward tutorial of Python that focuses on the basic knowledge needed to use Python for data analysis.
Statistical Learning using R – A downloadable book
I was looking for some books on Statistical Learning for a new course that I am preparing, and I came across a very interesting book titled “The Elements of Statistical Learning Data Mining, Inference, and Prediction” by Trevor Hastie, Robert Tibshirani, and Jerome Friedman. This book can be downloaded for free. I enjoyed reading this book since it is very well written and contains several examples. Additionally, data and R scripts used in the book are available for download in the book website.
Principles of Mathematical Economics – downloadable book
I received today an interesting book suggestion. The book titled “Principles of Mathematical Economics” is written by Professor Kam Yu (Lakehead University). This is a book about the basic math knowledge every economist should have. I find this book to be very concise and comprehensive at the same time. The examples provided are very good. In sum, I recommend this book for those interested in learning more useful math for economists.
Ernesto Lozardo’s new book: Ok, Roberto. Você venceu!
Professor Ernesto Lozardo has taught economics at EAESP-FGV since 1977. I took his Money, Credit, and Banking course when I was a junior at EAESP. To make a long story short, his knowledge and passion about economics and his will to put in practice good economic policies strongly motivated me to pursue a graduate education in economics.
That said, Prof. Lozardo’s new book titled “Ok, Roberto. Você venceu!” (published by Topbooks) is about Roberto Campos. He was one of the most notable Brazilian economists of the last century, not only in terms of designing development policies but also in terms of implementing them. In fact, his policies transformed Brazil from a very poor country in the late 1940s to a middle-income country in the mid 1970s.
I strongly recommend chapters 5, 6, and 7 for those interested in learning more about the institutional reforms conducted by Campos that led to strong economic growth in Brazil in the 1970s. Several of those institutions are still present in Brazil nowadays.
New book about Brazil’s Foreign Policy
A very interesting book about Brazil’s foreign policy edited by Funag and Ipea is available for download here. This book covers Brazil’s foreign policies after the 2008 crisis. Chapters 5 through 9 are of special interest for international economists. I strongly recommend this book for anyone interested in learning more about Brazil’s foreign affairs.
New Trade Agreement between Brazil and Chile
On November 21, 2018 Brazil and Chile signed a new trade agreement in Santiago, Chile. This new treaty expands the original agreement of 1996 that focused solely on the reduction of tariff barriers. Chile is the second largest trade partner of Brazil in South America, and in 2017 Brazil and Chile traded approximately 8.5 billion dollars in goods and services.
The new agreement is about 24 topics related to non-tariff barriers to trade in goods and services including electronic commerce, and intellectual property rights. Both countries agreed to exchange electronic customs paperwork and to recognize each other’s Operadores Economicos Autorizados. These measures will considerably expedite the customs procedures and reduce the customs clearing time. Another interesting item of the new treaty is the commitment to eliminate roaming charges for cell phone and data transmission. Additional information about this initiative can be found at Brazil’s MDIC webpage.
Trade Facilitation Agreement between Brazil and Peru
Today (11/27/2018) Brazil signed a trade facilitation agreement with Peru. Such agreement is related to the Operador Econômico Autorizado (OEA) program regulated in Brazil by the Instrução Normativa RFB nº 1.598/2015. The purposes of this type of agreement are a reduction in red tape and in the number and frequency of import and export shipment inspections, and therefore to foster international trade. Similar agreements have been signed between Brazil and other countries, like Bolivia in 2017. You can find more information about the Brazilian OEA program in the following link.
Stata Tutorial
Graphs in R
Carefully thought graphs and diagrams can help you make your point. R has very nice features when it comes to graphs. Nevertheless, things can get cumbersome quickly.
This first link provides a good explanation on how to make simple graphs. This other link contains an encyclopedic treatment of graphs in R.
Finally, in the event you are using R Studio and the plot refuses to show up, go to the Console and type “dev.off()” till you get an error message. Then, try plotting the graph again. Another solution is to restart R Studio. More on this issue can be found here.