edit si

analysis/paper/si.Rmd

@@ -33,12 +33,8 @@ csl: "../templates/vancouver.csl" # Insert path for the bib-style
 content: | 
   x pages, x figures
 always_allow_html: true
-header-includes:
-    - \usepackage{caption}
 ---
 
-\captionsetup[table]{labelformat=empty}
-
 Content: `r rmarkdown::metadata$content`
 
 ```{r setup, echo = FALSE, include = FALSE, message = FALSE}
@@ -163,7 +159,7 @@ For our results in the main paper, we first decompose the EXIOBASE national hous
 
 Step 1) Multiply 'mean consumption expenditure by income quintile' in purchasing power standard per household (pps hh) by the 'structure of consumption expenditure by income quintile and COICOP consumption purpose' (in 'parts per mille' or pm) to calculate the consumption expenditure structure in 'pps hh'. Then calculate the shares of eachincome quintile within each sector. Table S1 shows the two sector example, where 'pps hh' is multiplied by the shares of each sector ('parts per mille' divided by 1000) to calculate the expenditure on each sector per income quintile in 'pps hh' ('s1 (pps hh)' and 's2 (pps hh)'). 's1 (q share)' and 's2 (q share)' are each income quintile's share of the total amount of expenditure (in 'pps hh') on that sector, according to the HBS.
 
-```{r tableS1, results = "asis", tab.cap = NULL}
+```{r tableS1, tab.cap = "HBS structure with calculations of quintile shares per sector."}
 
 #"HBS structure with calculations of quintile shares per sector."
 
@@ -190,7 +186,6 @@ flextable(hbs) %>%
                     sector_1_shares = "s1 (q share)",
                     pps_hh_sector2 = "s2 (pps hh)",
                     sector_2_shares = "s2 (q share)") %>%
-  set_caption("Table S1: HBS structure with calculations of quintile shares per sector.") %>%
   fit_to_width(max_width = 7.5)
                             
 ```