Generate Time Series in R with existing year variable

Question

My Question

I would like to set an existing variable ( year ) at a time-series variable for use in regressions in R.

My data

I have a dataset (in data-frame format ) of country-level socioeconomic information from 1999 to 2013. Not every country has observations for every year. Some fill the entire range (1999-2013). Others do not.

The data look like this:

data:
year   country   economy       poverty
2011   Algeria   1.0814223     1.3310658
2012   Algeria   0.4172840     0.6206897
2013   Algeria   0.5652174     0.9222222
1999   Morocco   1.0814223     1.3310658
2000   Morocco   1.3310658     1.1468254
2001   Morocco   0.6206897     1.2805829
2002   Morocco   0.9222222     1.3310658
2003   Morocco   1.6500000     0.7612833
2004   Morocco   0.9126984     0.9768519
2005   Morocco   1.1388889     1.3310658
2006   Morocco   1.0500000     0.8011516
2007   Morocco   1.0458075     0.5761905
2008   Morocco   1.5017544     0.6222222
2009   Morocco   1.1666667     1.3310658
2010   Morocco   1.0527660     1.1468254
2011   Morocco   1.3611111     0.5761905
2012   Morocco   1.1666667     0.5761905
2013   Morocco   1.4137931     0.5761905

How can I tell R to treat these data as time-series? I have tried the following:

Setting the entire dataframe as a time series:

ts.data <- as.ts(data, start = 1999, end = 2013)

Setting a time-series variable within the dataset:

data$timeseries <- ts(data$year, start = 1999, end = 2013, frequency = 1)

Unfortunately, neither works.

I'm sure that this is a dumb question, and I apologize. Thank you in advance for your help!

Answer 1

Assuming you really do want to create a time series from this as stated in the question:

library(zoo)
z <- read.zoo(data, split = "country")

giving this "zoo" class object (continued after output):

> z
     economy.Algeria poverty.Algeria economy.Morocco poverty.Morocco
1999              NA              NA       1.0814223       1.3310658
2000              NA              NA       1.3310658       1.1468254
2001              NA              NA       0.6206897       1.2805829
2002              NA              NA       0.9222222       1.3310658
2003              NA              NA       1.6500000       0.7612833
2004              NA              NA       0.9126984       0.9768519
2005              NA              NA       1.1388889       1.3310658
2006              NA              NA       1.0500000       0.8011516
2007              NA              NA       1.0458075       0.5761905
2008              NA              NA       1.5017544       0.6222222
2009              NA              NA       1.1666667       1.3310658
2010              NA              NA       1.0527660       1.1468254
2011       1.0814223       1.3310658       1.3611111       0.5761905
2012       0.4172840       0.6206897       1.1666667       0.5761905
2013       0.5652174       0.9222222       1.4137931       0.5761905

or to convert to "ts" class:

tt <- as.ts(z)

Note: The input data in reproducible form is:

Lines <- "year   country   economy       poverty
2011   Algeria   1.0814223     1.3310658
2012   Algeria   0.4172840     0.6206897
2013   Algeria   0.5652174     0.9222222
1999   Morocco   1.0814223     1.3310658
2000   Morocco   1.3310658     1.1468254
2001   Morocco   0.6206897     1.2805829
2002   Morocco   0.9222222     1.3310658
2003   Morocco   1.6500000     0.7612833
2004   Morocco   0.9126984     0.9768519
2005   Morocco   1.1388889     1.3310658
2006   Morocco   1.0500000     0.8011516
2007   Morocco   1.0458075     0.5761905
2008   Morocco   1.5017544     0.6222222
2009   Morocco   1.1666667     1.3310658
2010   Morocco   1.0527660     1.1468254
2011   Morocco   1.3611111     0.5761905
2012   Morocco   1.1666667     0.5761905
2013   Morocco   1.4137931     0.5761905"

data <- read.table(text = Lines, header = TRUE)