How did Moldova’s parties spend their campaign money? Spending patterns in the 2025 elections

campaign finance

campaign spending

advertising

volunteers

elections

Moldova

This blog post looks at the spending side of Moldova’s 2025 parliamentary campaign. Using the official financial reports filed by electoral contestants, it shows how much each contestant spent, on what, and how differently well-funded and resource-poor contestants allocated their money. It is the second of a few posts based on my analysis in the Moldovan Analytical Digest.

Author

Sergiu Lipcean

Published

April 18, 2026

This is the second post based on my analysis in the Moldovan Analytical Digest (Lipcean, 2026). The first post looked at how contestants raised money in Moldova’s 2025 parliamentary elections. Here I look at the other side: how much they spent, what they spent it on, and whether contestants with a lot of money spent differently from those with little. As before, the analysis uses the official financial reports that contestants filed with the Central Electoral Commission (CEC) (Comisia Electorală Centrală, 2025b), and therefore covers only declared spending. The figures cover the same 21 contestants as in the previous post.

Acronyms of electoral contestants

Acronym	Electoral contestant
ALDE	Alliance of Liberals and Democrats for Europe
AM	Moldovans Alliance
AUR	Alliance for the Union of Romanians
BEA	Alternative Bloc
BEP	Patriotic Electoral Bloc
BEÎ	Together Bloc
CI-AN	Independent candidate, Andrei Năstase
CI-OS	Independent candidate, Olesea Stamate
CI-TC	Independent candidate, Tatiana Crețu
CI-VS	Independent candidate, Victoria Sanduța
CUB	Coalition for Unity and Welfare
LOC	League of Cities and Communes
MRM	Respect Moldova Movement
NOI	New Historical Option
PAS	Party of Action and Solidarity
PDA	Democracy at Home Party
PL	Liberal Party
PN	Our Party
PNM	National Moldovan Party
PSDE	European Social Democratic Party
UCSM	Christian-Social Union of Moldova

How much did contestants spend?

The law capped each contestant’s spending at 0.1% of state budget revenues: MDL 75,932,486, or about €3.9 million (Comisia Electorală Centrală, 2025a). That is roughly MDL 28 (€1.4) per registered voter. In the 2021 elections the cap was half as large as a share of the budget (0.05%, or MDL 20,707,700 (Comisia Electorală Centrală, 2021)), so the 2025 cap was about 3.7 times higher in lei. In practice, nobody came close to it. The biggest spender, the Patriotic Electoral Bloc (BEP), used 41% of the cap, and the Party of Action and Solidarity (PAS), the party in government, 33%. Most contestants spent less than 2%.

Together, electoral competitors reported about €5.0 million in campaign spending. Given the interchangeability of income and spending totals, reported spending matches reported income almost to the euro (the largest difference is about €10), so the ranking is the same as for income. The inequality in fundraising described in the previous post is therefore also an inequality in spending. The interesting question is how contestants allocated their campaign money for different purposes to win the voters’ hearts and endorsement.

Where did the money go?

Figure 1 breaks spending down into four broad categories. Panel A ranks contestants based on spending budgets from the largest to the smallest. It also shows the distribution of spending categories in absolute numbers. Panel B displays the distribution of spending categories in percentage, which provides a more nuanced perspective on how contestants prioritised the allocation of campaign money for different purposes. To keep the figure readable, I show the three largest categories separately and lump all the others together. The three categories that dominate spending priorities include: volunteer activities (44% of all reported spending), broadcast advertisements (25%) and promotional materials (19%). Together they account for 89% of all campaign spending. The remaining categories are insignificant: in-kind goods and services account for 5%, transport for 2%, while premises, personnel and legal fees are each below 0.5%.

Two stacked bar charts of campaign spending by contestant. Panel A shows absolute amounts in thousand euro, with BEP and PAS above 1.2 million and most contestants below 100 thousand. Panel B shows the share of volunteer activities, broadcast advertisements, promotional materials and all other categories. — Figure 1: Campaign spending of electoral contestants in Moldova’s 2025 parliamentary elections, by spending category. Panel A shows absolute amounts (the label is the net total spending), panel B the share of each category. The three largest categories are shown separately, all others are grouped.

Volunteers

Volunteer work represents the largest spending item and is reported on both sides of the campaign budget, as income (what supporters contribute) and as spending (the value of their work, as reported by the contestant). This is also the category where the gap between electoral contestants is widest. For BEP, volunteer activities make up 66% of reported spending, and for the Respect Moldova Movement (MRM) 57%. For PAS, the party in government, it accounts for 28% of expenses. The majority of smaller contestants report little or no volunteer activity at all. We know that the ability to mobilize volunteers is a sign of relatively strong organisation.

What type of work did volunteers carry out? In the digest I used the detailed campaign reports of each contestant to show that about three quarters of volunteer activities, around 30,000 in all, consisted in handing out campaign materials in direct contact with voters. More than 6,000 worked as representatives at polling stations, and the rest helped with media, logistics and other support (Lipcean, 2026).

Broadcast advertisements and promotional materials

Broadcast advertisements are the second biggest item, and here the picture is different. PAS spent €503,710 on producing and airing commercials, 39% of its spending, more than any other contestant in euros. The other big spenders had other priorities: BEP devoted only 7% of its spending to commercials, BEA 26% and PN 31%. Among the less well-funded contestants, commercials were typically a larger share of the budget than for their wealthier counterparts. Outside the six best-funded contestants, the typical share spent on broadcast advertisements revolves around 46%, although several of them spent on broadcasting ads more than two thirds of their entire budget. Paid commercials were regarded by electoral competitors with little resources and limited organisation capacity to get campaign visibility to offset the shortage of a volunteer network.

Promotional materials, such as printed leaflets and posters, constitute the third spending category. Across the six best-funded contestants, they account for between 13% and 37% of spending, which suggests that such outlays are a routine cost for contestants with an established organisational structure.

Figure 2 displays the share of campaign spending for each of the two dominant categories – broadcasting ads and volunteer work – against each other. Each point is a contestant, located by the share of its spending for volunteer activities (horizontal axis) and to broadcast advertisements (vertical axis), while the size and colour of each point show how much the respective contestant spent in total. As the plot shows, contestants spread along a diagonal, from campaigns investing almost exclusively in advertisements (upper left) to campaigns prioritizing volunteer work (lower right). The well-funded competitors and big spenders are scattered in different places: BEP and MRM relied mostly on volunteers, PAS and BEA are in the middle, while most poorly funded contestants are located in the top left corner.

A scatter plot where each point is a contestant. The horizontal axis shows the share of spending on volunteer activities, the vertical axis the share on broadcast advertisements. Point size shows total spending. BEP is at the far right, many small contestants are in the upper left. — Figure 2: Campaign spending strategies of electoral contestants in Moldova’s 2025 parliamentary elections: share of spending on volunteer activities and on broadcast advertisements. The size of the point shows total spending.

What this means for competition

Given that campaign spending represents the flip side of fundraising, it reflects the same disparities in resources: several contestants spent considerably more than most of other competitors. The top-tier spenders had more options regarding how to allocate their funds between different categories. However, as data show, they had different preferences on how to combine volunteer work, media coverage and organisation. In contrast, contestants with limited funds had a much narrower choice. Without an extensive organisation and a narrow volunteer pool, they channeled most of their money into paid commercials to increase visibility.

These resource disparities raise a critical question: do they ultimately translate into votes? I provide a tentative answer in the next post.

References

Comisia Electorală Centrală. (2021). Cu privire la stabilirea plafonului general al mijloacelor financiare ce pot fi transferate în contul „Fond electoral” al concurenților electorali la alegerile parlamentare anticipate din 11 iulie 2021. https://a.cec.md/ro/cu-privire-la-stabilirea-plafonului-general-al-mijloacelor-financiare-ce-2751_99328.html

Comisia Electorală Centrală. (2025a). Cu privire la stabilirea plafonului general al mijloacelor financiare ce pot fi transferate în contul „Fond electoral” și utilizate de concurenții electorali la alegerile parlamentare din data de 28 septembrie 2025. https://a.cec.md/ro/cu-privire-la-stabilirea-plafonului-general-al-mijloacelor-financiare-ce-2751_114256.html

Comisia Electorală Centrală. (2025b). Sistemul informatic “Control financiar”. https://finante.cec.md/reports.aspx

Lipcean, S. (2026). Campaign financing in Moldova’s 2025 parliamentary elections. Moldovan Analytical Digest, 5, 2–17. https://doi.org/10.3929/ethz-c-000793910

--- title: "How did Moldova's parties spend their campaign money? Spending patterns in the 2025 elections" description: "This blog post looks at the spending side of Moldova's 2025 parliamentary campaign. Using the official financial reports filed by electoral contestants, it shows how much each contestant spent, on what, and how differently well-funded and resource-poor contestants allocated their money. It is the second of a few posts based on my analysis in the Moldovan Analytical Digest." author: - name: Sergiu Lipcean url: https://sergiulipcean.github.io/ orcid: 0000-0002-8944-6505 date: "2026-04-18" categories: [campaign finance, campaign spending, advertising, volunteers, elections, Moldova] # self-defined categories draft: false # setting this to `true` will prevent the post from appearing on the listing page! link-citations: true csl: apa.csl linkcolor: "#0F4D92" urlcolor: "#0F4D92" bibliography: references.bib --- ```{=html} <style type = text/css> body{line-height: 1.5em; font-size: 14pt; font-family: Trebuchet MS; text-align: justify;} </style> ``` ```{r setup, include=FALSE} knitr::opts_chunk$set(echo = FALSE, warning = FALSE, message = FALSE, fig.width = 10, fig.height = 10, dev = "ragg_png") ``` ```{r} # Download R packages library(tidyverse) library(openxlsx) library(patchwork) library(ggrepel) library(scales) library(extrafont) # Make the Windows fonts available to the plots (Trebuchet MS, as in the text) loadfonts(device = "win", quiet = TRUE) ``` ```{r} # Spending data: one row per contestant and spending category (amounts in MDL and EUR) # MM and BUN are left out, as in the previous post spending_data <- read.xlsx("spending_data_long.xlsx") %>% filter(!Competitor_Acronym %in% c("MM", "BUN")) %>% # tidy two category labels mutate(spending_category_en = case_match(spending_category_en, "Production/airing comercials" ~ "Broadcast advertisements", "Premises: rent/maintenance" ~ "Premises", .default = spending_category_en)) %>% group_by(Competitor_Acronym) %>% # total = net spending, stack = sum of the positive items mutate(total_eur = sum(Amount_EUR), total_mdl = sum(amount), stack_eur = sum(Amount_EUR[Amount_EUR >= 0])) %>% ungroup() %>% mutate(Competitor_Acronym = fct_reorder(Competitor_Acronym, total_eur), # keep the three largest categories and group the rest category = fct_lump_n(spending_category_en, n = 3, w = pmax(Amount_EUR, 0), other_level = "All other categories"), category = fct_relevel(category, "All other categories", "Promotional materials", "Broadcast advertisements", "Volunteer activities")) # One row per contestant with total spending spending_totals <- spending_data %>% distinct(Competitor_Acronym, total_eur, total_mdl, stack_eur) # Share of each category in the spending of each contestant (rows = contestants) spending_share <- spending_data %>% filter(Amount_EUR >= 0) %>% mutate(share = Amount_EUR / sum(Amount_EUR), .by = Competitor_Acronym) %>% select(Competitor_Acronym, spending_category_en, share) %>% pivot_wider(names_from = spending_category_en, values_from = share) %>% column_to_rownames("Competitor_Acronym") # Amounts in euro by contestant and category (rows = contestants) spending_eur <- spending_data %>% select(Competitor_Acronym, spending_category_en, Amount_EUR) %>% pivot_wider(names_from = spending_category_en, values_from = Amount_EUR) %>% column_to_rownames("Competitor_Acronym") # Share of each category in the spending of all contestants category_share <- spending_data %>% filter(Amount_EUR >= 0) %>% summarise(eur = sum(Amount_EUR), .by = spending_category_en) %>% mutate(share = eur / sum(eur)) %>% select(spending_category_en, share) %>% deframe() # Spending cap per contestant (MDL) set by the CEC for the 2025 and 2021 elections cap_2025 <- 75932486 cap_2021 <- 20707700 spending_totals <- spending_totals %>% mutate(cap_share = total_mdl / cap_2025) # Six best-funded contestants versus all others: share of spending on broadcast advertisements top6 <- c("BEP", "PAS", "BEA", "PN", "MRM", "AM") broadcast_others <- spending_share[!rownames(spending_share) %in% top6, "Broadcast advertisements"] promo_top6 <- spending_share[top6, "Promotional materials"] ``` This is the second post based on my analysis in the Moldovan Analytical Digest [@lipcean2026]. The [first post](../2026-03-15-moldova-2025-campaign-income/index.qmd) looked at how contestants raised money in Moldova's 2025 parliamentary elections. Here I look at the other side: how much they spent, what they spent it on, and whether contestants with a lot of money spent differently from those with little. As before, the analysis uses the official financial reports that contestants filed with the Central Electoral Commission (CEC) [@cec2025financial], and therefore covers only declared spending. The figures cover the same `r nrow(spending_totals)` contestants as in the previous post. ::: {.callout-note collapse="true"} ## Acronyms of electoral contestants ```{r} read.xlsx("acronims.xlsx") %>% rename(Acronym = party_acronym, `Electoral contestant` = party_name_en) %>% knitr::kable() ``` ::: ***How much did contestants spend?*** The law capped each contestant's spending at 0.1% of state budget revenues: MDL 75,932,486, or about €3.9 million [@cec2025cap]. That is roughly MDL 28 (€1.4) per registered voter. In the 2021 elections the cap was half as large as a share of the budget (0.05%, or MDL 20,707,700 [@cec2021cap]), so the 2025 cap was about `r round(cap_2025 / cap_2021, 1)` times higher in lei. In practice, nobody came close to it. The biggest spender, the Patriotic Electoral Bloc (BEP), used `r percent(max(spending_totals$cap_share), accuracy = 1)` of the cap, and the Party of Action and Solidarity (PAS), the party in government, `r percent(spending_totals$cap_share[spending_totals$Competitor_Acronym == "PAS"], accuracy = 1)`. Most contestants spent less than 2%. Together, electoral competitors reported about `r dollar(sum(spending_totals$total_eur) / 1e6, prefix = "€", accuracy = 0.1, suffix = " million")` in campaign spending. Given the interchangeability of income and spending totals, reported spending matches reported income almost to the euro (the largest difference is about €10), so the ranking is the same as for income. The inequality in fundraising described in the previous post is therefore also an inequality in spending. The interesting question is how contestants allocated their campaign money for different purposes to win the voters' hearts and endorsement. ***Where did the money go?*** @fig-spending breaks spending down into four broad categories. Panel A ranks contestants based on spending budgets from the largest to the smallest. It also shows the distribution of spending categories in absolute numbers. Panel B displays the distribution of spending categories in percentage, which provides a more nuanced perspective on how contestants prioritised the allocation of campaign money for different purposes. To keep the figure readable, I show the three largest categories separately and lump all the others together. The three categories that dominate spending priorities include: volunteer activities (`r percent(category_share[["Volunteer activities"]], accuracy = 1)` of all reported spending), broadcast advertisements (`r percent(category_share[["Broadcast advertisements"]], accuracy = 1)`) and promotional materials (`r percent(category_share[["Promotional materials"]], accuracy = 1)`). Together they account for `r percent(category_share[["Volunteer activities"]] + category_share[["Broadcast advertisements"]] + category_share[["Promotional materials"]], accuracy = 1)` of all campaign spending. The remaining categories are insignificant: in-kind goods and services account for `r percent(category_share[["In-kind: goods/services"]], accuracy = 1)`, transport for `r percent(category_share[["Transport"]], accuracy = 1)`, while premises, personnel and legal fees are each below 0.5%. ```{r} #| label: fig-spending #| fig-cap: "Campaign spending of electoral contestants in Moldova's 2025 parliamentary elections, by spending category. Panel A shows absolute amounts (the label is the net total spending), panel B the share of each category. The three largest categories are shown separately, all others are grouped." #| fig-alt: "Two stacked bar charts of campaign spending by contestant. Panel A shows absolute amounts in thousand euro, with BEP and PAS above 1.2 million and most contestants below 100 thousand. Panel B shows the share of volunteer activities, broadcast advertisements, promotional materials and all other categories." #| fig-height: 4.5 #| fig-width: 8 # Panel A: absolute amounts absolute_sp <- spending_data %>% filter(Amount_EUR >= 0) %>% ggplot(aes(x = Competitor_Acronym, y = Amount_EUR / 1000, fill = fct_rev(category))) + geom_col() + geom_text(data = spending_totals, aes(x = Competitor_Acronym, y = stack_eur / 1000, label = comma(total_eur / 1000, accuracy = 1)), inherit.aes = FALSE, hjust = -0.1, size = 3, family = "Trebuchet MS") + scale_y_continuous(breaks = seq(0, 1500, 300), labels = comma, expand = expansion(mult = c(0, 0.12))) + scale_fill_viridis_d(name = "Spending categories", end = 0.9) + guides(fill = guide_legend(reverse = TRUE)) + coord_flip() + theme_light(base_family = "Trebuchet MS") + theme( panel.grid.minor = element_blank(), panel.grid.major = element_line(linetype = 3), legend.background = element_rect(fill = "transparent"), plot.title = element_text(size = 12), legend.key.height = unit(0.8, "lines"), legend.key.width = unit(0.8, "lines"), legend.position = "inside", legend.position.inside = c(0.65, 0.25) ) + labs(title = "A: Absolute numbers", x = "", y = "€ thousand") # Panel B: share of each category in the spending of each contestant relative_sp <- spending_data %>% filter(Amount_EUR >= 0) %>% ggplot(aes(x = Competitor_Acronym, y = Amount_EUR, fill = fct_rev(category))) + geom_col(position = position_fill()) + scale_y_continuous(labels = percent) + scale_fill_viridis_d(name = "Spending categories", end = 0.9) + coord_flip() + theme_light(base_family = "Trebuchet MS") + theme( axis.text.y = element_blank(), plot.title = element_text(size = 12), panel.grid.minor = element_blank(), panel.grid.major = element_line(linetype = 3), legend.position = "none" ) + labs(title = "B: Percentage", x = "", y = "Percentage") # Combine both panels absolute_sp + relative_sp ``` ***Volunteers*** Volunteer work represents the largest spending item and is reported on both sides of the campaign budget, as income (what supporters contribute) and as spending (the value of their work, as reported by the contestant). This is also the category where the gap between electoral contestants is widest. For BEP, volunteer activities make up `r percent(spending_share["BEP", "Volunteer activities"], accuracy = 1)` of reported spending, and for the Respect Moldova Movement (MRM) `r percent(spending_share["MRM", "Volunteer activities"], accuracy = 1)`. For PAS, the party in government, it accounts for `r percent(spending_share["PAS", "Volunteer activities"], accuracy = 1)` of expenses. The majority of smaller contestants report little or no volunteer activity at all. We know that the ability to mobilize volunteers is a sign of relatively strong organisation. What type of work did volunteers carry out? In the digest I used the detailed campaign reports of each contestant to show that about three quarters of volunteer activities, around 30,000 in all, consisted in handing out campaign materials in direct contact with voters. More than 6,000 worked as representatives at polling stations, and the rest helped with media, logistics and other support [@lipcean2026]. ***Broadcast advertisements and promotional materials*** Broadcast advertisements are the second biggest item, and here the picture is different. PAS spent `r dollar(spending_eur["PAS", "Broadcast advertisements"], prefix = "€", accuracy = 1)` on producing and airing commercials, `r percent(spending_share["PAS", "Broadcast advertisements"], accuracy = 1)` of its spending, more than any other contestant in euros. The other big spenders had other priorities: BEP devoted only `r percent(spending_share["BEP", "Broadcast advertisements"], accuracy = 1)` of its spending to commercials, BEA `r percent(spending_share["BEA", "Broadcast advertisements"], accuracy = 1)` and PN `r percent(spending_share["PN", "Broadcast advertisements"], accuracy = 1)`. Among the less well-funded contestants, commercials were typically a *larger* share of the budget than for their wealthier counterparts. Outside the six best-funded contestants, the typical share spent on broadcast advertisements revolves around `r percent(median(broadcast_others), accuracy = 1)`, although several of them spent on broadcasting ads more than two thirds of their entire budget. Paid commercials were regarded by electoral competitors with little resources and limited organisation capacity to get campaign visibility to offset the shortage of a volunteer network. Promotional materials, such as printed leaflets and posters, constitute the third spending category. Across the six best-funded contestants, they account for between `r percent(min(promo_top6), accuracy = 1)` and `r percent(max(promo_top6), accuracy = 1)` of spending, which suggests that such outlays are a routine cost for contestants with an established organisational structure. @fig-strategies displays the share of campaign spending for each of the two dominant categories -- broadcasting ads and volunteer work -- against each other. Each point is a contestant, located by the share of its spending for volunteer activities (horizontal axis) and to broadcast advertisements (vertical axis), while the size and colour of each point show how much the respective contestant spent in total. As the plot shows, contestants spread along a diagonal, from campaigns investing almost exclusively in advertisements (upper left) to campaigns prioritizing volunteer work (lower right). The well-funded competitors and big spenders are scattered in different places: BEP and MRM relied mostly on volunteers, PAS and BEA are in the middle, while most poorly funded contestants are located in the top left corner. ```{r} #| label: fig-strategies #| fig-cap: "Campaign spending strategies of electoral contestants in Moldova's 2025 parliamentary elections: share of spending on volunteer activities and on broadcast advertisements. The size of the point shows total spending." #| fig-alt: "A scatter plot where each point is a contestant. The horizontal axis shows the share of spending on volunteer activities, the vertical axis the share on broadcast advertisements. Point size shows total spending. BEP is at the far right, many small contestants are in the upper left." #| fig-height: 4 #| fig-width: 7 spending_share %>% rownames_to_column("Competitor_Acronym") %>% left_join(spending_totals, by = "Competitor_Acronym") %>% ggplot(aes(x = `Volunteer activities`, y = `Broadcast advertisements`, size = total_eur / 1000, colour = total_eur / 1000)) + geom_point(alpha = 0.8) + geom_text_repel(aes(label = Competitor_Acronym), colour = "grey30", size = 3, family = "Trebuchet MS") + scale_x_continuous(labels = percent) + scale_y_continuous(labels = percent) + scale_size_continuous(name = "Total spending\n€ thousand", breaks = c(10, 50, 250, 500, 1000, 1500), labels = comma, range = c(1, 10)) + scale_colour_viridis_c(name = "Total spending\n€ thousand", breaks = c(10, 50, 250, 500, 1000, 1500), labels = comma, end = 0.9) + guides(size = guide_legend(), colour = guide_legend()) + # merge both legends labs(x = "Share of spending on volunteer activities", y = "Share of spending on broadcast advertisements") + theme_light(base_family = "Trebuchet MS") + theme(panel.grid.minor = element_blank(), panel.grid.major = element_line(linetype = 3)) ``` ***What this means for competition*** Given that campaign spending represents the flip side of fundraising, it reflects the same disparities in resources: several contestants spent considerably more than most of other competitors. The top-tier spenders had more options regarding how to allocate their funds between different categories. However, as data show, they had different preferences on how to combine volunteer work, media coverage and organisation. In contrast, contestants with limited funds had a much narrower choice. Without an extensive organisation and a narrow volunteer pool, they channeled most of their money into paid commercials to increase visibility. These resource disparities raise a critical question: do they ultimately translate into votes? I provide a tentative answer in the next post. ::: {#references} :::